Project Part 2

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This notebook contains the code samples found in Chapter 3, Section 5 of Deep Learning with R. Note that the original text features far more content, in particular further explanations and figures: in this notebook, you will only find source code and related comments.

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Data Exploration & Preparation

• Our goal in the second part of the assignment is to predict how good a (new) customer will pay back their credit card depts. In the data set application data from current customers (the first 18 attributes) together with their status (last attribute; target) are given.
  
• The attributes from the applications are

Attribute Name	Explanation	Remarks
ID	Client	number
CODE_GENDER	Gender
FLAG_OWN_CAR	Is there a car
FLAG_OWN_REALTY	Is there a property
CNT_CHILDREN	Number of children
AMT_INCOME_TOTAL	Annual income
NAME_INCOME_TYPE	Income category
NAME_EDUCATION_TYPE	Education level
NAME_FAMILY_STATUS	Marital status
NAME_HOUSING_TYPE	Way of living
DAYS_BIRTH	Birthday	Count backwards from current day (0), -1 means yesterday
DAYS_EMPLOYED	Start date of employment	Count backwards from current day(0). If positive, it means the person unemployed.
FLAG_MOBIL	Is there a mobile phone
FLAG_WORK_PHONE	Is there a work phone
FLAG_PHONE	Is there a phone
FLAG_EMAIL	Is there an email
OCCUPATION_TYPE	Occupation
CNT_FAM_MEMBERS	Family size

• The last attribute status contains the “pay-back behavior”, i.e. when did that customer pay back their depts:
  • 0: 1-29 days past due
  • 1: 30-59 days past due
  • 2: 60-89 days overdue
  • 3: 90-119 days overdue
  • 4: 120-149 days overdue
  • 5: Overdue or bad debts, write-offs for more than 150 days
  • C: paid off that month
  • X: No loan for the month Please note: We are learning only the pay-back behavior. The decision, i.e. if we accept a customer or not, is done in another process step – not here!

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Main task

• Design your network. Why did you use a feed-forward network, or a convolutional or recursive network – and why not?
  
• Use k-fold validation (with k = 10) to find the best hyperparameters for your network.
• Use the average of the accuracy to evaluate the performance of your trained network.
• Find a “reasonable” good model. Argue why that model is reasonable. If you are not able to find a reasonable good model, explain what you all did to find a good model and argue why you think that’s not a good model.
  
• Save your trained neural network with save_model_hdf5. Also save your data sets you used for training, testing and validation.

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Some hints

• Data preprocessing is easier here; no feature engineering is needed.
• You may be able to reuse parts of the exercises we used in our examples during lectures.
• All in- and output values need to be floating numbers (or integers in exceptions) in the range of [0,1].
• Please note that a neural network expects a R matrix or vector, not data frames. Transform your data (e.g. a data frame) into a matrix with data.matrix if needed.
  
• There are some models which show an accuracy higher than 90% (!) for training (and test) data – after learning more than 1000 epochs.

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Important notes

• Single-label, Multiclass classification problem on page 73 in Deep Learning with R
• Spaces must be removed in between ‘{r}' and '’, else an error with ‘’ will be produced
• K-Fold Validation on page 83ff and 94ff in Deep Learning with R
• Page 110, use Last-Layer activation softmax and loss function categorical_crossentropy
• Convolutional network ausgeschlossen, weil hauptsächlich Pattern recognition/image classification
• Recursive ausgeschlossen, weil hauptsächlich für TimeSeries-Vorhersagen verwendet, oder für Vorhersagen
• Feed-Forward, weil Classification-Task

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Data import

#install.packages("tidymodels")
#install.packages("themis")
library(here)
library(tidyverse)
library(ggplot2)
library(dplyr)
library(tensorflow)
library(tfdatasets)
library(tidymodels)
library(keras)
library(caret)
library(themis)
#LOAD DATA
setwd(getwd())
dataIn = "../Data/Dataset-part-2.csv"
data_in <- read.csv(dataIn,header = TRUE, sep =',')
#View(data_in)
data <- data.frame(data_in)
summary(data)

       ID          CODE_GENDER        FLAG_OWN_CAR       FLAG_OWN_REALTY     CNT_CHILDREN     AMT_INCOME_TOTAL 
 Min.   :5008804   Length:67614       Length:67614       Length:67614       Min.   : 0.0000   Min.   :  26100  
 1st Qu.:5465941   Class :character   Class :character   Class :character   1st Qu.: 0.0000   1st Qu.: 112500  
 Median :5954270   Mode  :character   Mode  :character   Mode  :character   Median : 0.0000   Median : 157500  
 Mean   :5908133                                                            Mean   : 0.4206   Mean   : 178867  
 3rd Qu.:6289080                                                            3rd Qu.: 1.0000  
 Max.   :7965248                                                            Max.   :19.0000   Max.   :6750000  
 NAME_INCOME_TYPE   NAME_EDUCATION_TYPE NAME_FAMILY_STATUS NAME_HOUSING_TYPE    DAYS_BIRTH     DAYS_EMPLOYED   
 Length:67614       Length:67614        Length:67614       Length:67614       Min.   :-25201   Min.   :-17531  
 Class :character   Class :character    Class :character   Class :character   1st Qu.:-19438   1st Qu.: -2886  
 Mode  :character   Mode  :character    Mode  :character   Mode  :character   Median :-15592   Median : -1305  
                                                                              Mean   :-15914   Mean   : 62022  
                                                                              3rd Qu.:-12347   3rd Qu.:  -321  
                                                                              Max.   : -7489   Max.   :365243  
   FLAG_MOBIL FLAG_WORK_PHONE    FLAG_PHONE       FLAG_EMAIL     OCCUPATION_TYPE    CNT_FAM_MEMBERS 
 Min.   :1    Min.   :0.0000   Min.   :0.0000   Min.   :0.0000   Length:67614       Min.   : 1.000  
 1st Qu.:1    1st Qu.:0.0000   1st Qu.:0.0000   1st Qu.:0.0000   Class :character   1st Qu.: 2.000  
 Median :1    Median :0.0000   Median :0.0000   Median :0.0000   Mode  :character   Median : 2.000  
 Mean   :1    Mean   :0.2028   Mean   :0.2742   Mean   :0.1005                      Mean   : 2.174  
 3rd Qu.:1    3rd Qu.:0.0000   3rd Qu.:1.0000   3rd Qu.:0.0000                      3rd Qu.: 3.000  
 Max.   :1    Max.   :1.0000   Max.   :1.0000   Max.   :1.0000                      Max.   :20.000  
    status         
 Length:67614      
 Class :character  
 Mode  :character  
                   
                   
                   

plot(data$status)

##Cleanup

# Check for duplicates 
sum(duplicated(data))

[1] 0

# No duplicates

#Remove ID (irrelevant) and FLAG_MOBIL (always 1)
data <- data %>% select(-ID, -FLAG_MOBIL)
cols <- c("CODE_GENDER","FLAG_OWN_CAR","FLAG_OWN_REALTY","NAME_INCOME_TYPE","NAME_EDUCATION_TYPE", "NAME_FAMILY_STATUS", "NAME_HOUSING_TYPE","FLAG_WORK_PHONE","FLAG_PHONE","FLAG_EMAIL", "OCCUPATION_TYPE","status")
cols

 [1] "CODE_GENDER"         "FLAG_OWN_CAR"        "FLAG_OWN_REALTY"     "NAME_INCOME_TYPE"   
 [5] "NAME_EDUCATION_TYPE" "NAME_FAMILY_STATUS"  "NAME_HOUSING_TYPE"   "FLAG_WORK_PHONE"    
 [9] "FLAG_PHONE"          "FLAG_EMAIL"          "OCCUPATION_TYPE"     "status"             

data[cols] <- lapply(data[cols],factor)

# Replacing empty values with "Unknown"
levels(data$OCCUPATION_TYPE) <- c(levels(data$OCCUPATION_TYPE), "Unknown")
data$OCCUPATION_TYPE[is.na(data$OCCUPATION_TYPE)] <- "Unknown"

# Replacing C and X in Status
levels(data$status)[levels(data$status)=="C"] <- "6"
#data$status[data$status == "X"] <- 7
levels(data$status)[levels(data$status)=="X"] <- "7"
# #Convert factors into numericals
# data %<>% mutate_if(is.factor, as.numeric)

summary(data)

 CODE_GENDER FLAG_OWN_CAR FLAG_OWN_REALTY  CNT_CHILDREN     AMT_INCOME_TOTAL              NAME_INCOME_TYPE
 F:43924     N:43107      N:21090         Min.   : 0.0000   Min.   :  26100   Commercial associate:15640  
 M:23690     Y:24507      Y:46524         1st Qu.: 0.0000   1st Qu.: 112500   Pensioner           :11982  
                                          Median : 0.0000   Median : 157500   State servant       : 5044  
                                          Mean   : 0.4206   Mean   : 178867   Student             :    4  
                                          3rd Qu.: 1.0000   3rd Qu.: 225000   Working             :34944  
                                          Max.   :19.0000   Max.   :6750000                               
                                                                                                          
                    NAME_EDUCATION_TYPE            NAME_FAMILY_STATUS           NAME_HOUSING_TYPE
 Academic degree              :   38    Civil marriage      : 6016    Co-op apartment    :  227  
 Higher education             :16890    Married             :44906    House / apartment  :60307  
 Incomplete higher            : 2306    Separated           : 4125    Municipal apartment: 2303  
 Lower secondary              :  716    Single / not married: 9528    Office apartment   :  587  
 Secondary / secondary special:47664    Widow               : 3039    Rented apartment   : 1020  
                                                                      With parents       : 3170  
                                                                                                 
   DAYS_BIRTH     DAYS_EMPLOYED    FLAG_WORK_PHONE FLAG_PHONE FLAG_EMAIL    OCCUPATION_TYPE  CNT_FAM_MEMBERS 
 Min.   :-25201   Min.   :-17531   0:53904         0:49071    0:60819    Unknown    :20699   Min.   : 1.000  
 1st Qu.:-19438   1st Qu.: -2886   1:13710         1:18543    1: 6795    Laborers   :12425   1st Qu.: 2.000  
 Median :-15592   Median : -1305                                         Sales staff: 6899   Median : 2.000  
 Mean   :-15914   Mean   : 62022                                         Core staff : 6059   Mean   : 2.174  
 3rd Qu.:-12347   3rd Qu.:  -321                                         Managers   : 4950   3rd Qu.: 3.000  
 Max.   : -7489   Max.   :365243                                         Drivers    : 4427   Max.   :20.000  
                                                                         (Other)    :12155                   
     status     
 0      :52133  
 1      : 6491  
 7      : 5790  
 6      : 1805  
 2      :  712  
 5      :  374  
 (Other):  309  

Preprocessing

set.seed(1)
trainIndex <- initial_split(data, prop = 0.8, strata = status) 
trainingSet <- training(trainIndex)
testSet <- testing(trainIndex)
status_folds <- vfold_cv(trainingSet, v = 10, strata = status)
status_folds

#  10-fold cross-validation using stratification 

# Remove outliers (Out of 1.5x Interquartile Range) only on training set
# CNT_CHILDREN
boxplot(trainingSet$CNT_CHILDREN, horizontal=TRUE, main="CNT_CHILDREN")

Q1_Child <- quantile(trainingSet$CNT_CHILDREN, .25)
Q3_Child <- quantile(trainingSet$CNT_CHILDREN, .75)
IQR_Child <- IQR(trainingSet$CNT_CHILDREN)
# Now we keep the values within 1.5*IQR of Q1 and Q3
trainingSet <- subset(trainingSet, trainingSet$CNT_CHILDREN > (Q1_Child - 1.5*IQR_Child) & trainingSet$CNT_CHILDREN < (Q3_Child + 1.5*IQR_Child))
dim(trainingSet)

[1] 53330    17

# AMT_INCOME_TOTAL
boxplot(trainingSet$AMT_INCOME_TOTAL, horizontal=TRUE, main="AMT_INCOME_TOTAL")

Q1_AIT <- quantile(trainingSet$AMT_INCOME_TOTAL, .25)
Q3_AIT <- quantile(trainingSet$AMT_INCOME_TOTAL, .75)
IQR_AIT <- IQR(trainingSet$AMT_INCOME_TOTAL)
# Now we keep the values within 1.5*IQR of Q1 and Q3
trainingSet <- subset(trainingSet, trainingSet$AMT_INCOME_TOTAL > (Q1_AIT - 1.5*IQR_AIT) & trainingSet$AMT_INCOME_TOTAL < (Q3_AIT + 1.5*IQR_AIT))
dim(trainingSet)

[1] 51748    17

set.seed(5)
preprocRecipe <-
  recipe(status ~., data = data) %>%
  step_dummy(all_nominal(), -status,  one_hot = TRUE) %>%
  step_range(all_predictors(), -all_nominal(), min = 0, max = 1)%>%
 # step_downsample(status, over_ratio = 1) %>%
  step_smote(status, over_ratio = 1, skip=TRUE) %>%
 # step_smotenc(status, over_ratio = 1) %>%
 #step_adasyn(status, over_ratio = 1) %>%
 #step_nearmiss(status, over_ratio = 1) %>%
   
  step_dummy(status,  one_hot = TRUE)# %>%

In this step the above defined receipt is extracted using the prep() function, and then use the bake() function to transform a set of data based on that recipe.

# retain = TRUE and new_data = NULL ensures that pre-processed trainingSet is returned 
trainingSet_processed <- preprocRecipe %>%
  prep(trainingSet, retain = TRUE) %>%
  bake(new_data = NULL)
testSet_processed <- preprocRecipe %>%
  prep(testSet) %>%
  bake(new_data =testSet)

#summary(trainingSet_processed)

Check data

# summarize the class distribution
percentage <- 100-prop.table(table(data$status)) * 100
cbind(freq=table(data$status), percentage=percentage)

   freq percentage
0 52133   22.89615
1  6491   90.39992
2   712   98.94696
3   195   99.71160
4   114   99.83140
5   374   99.44686
6  1805   97.33043
7  5790   91.43668

class_weights <- list("0"=1,"1"=100)

# Turn data frame into data matrix
matrix_data <- trainingSet_processed %>% select(-tail(names(trainingSet_processed), 8))
matrix_targets <- trainingSet_processed %>% select(tail(names(trainingSet_processed), 8))

matrix_data_test  <- testSet_processed %>% select(-tail(names(testSet_processed), 8))
matrix_targets_test  <- testSet_processed %>% select(tail(names(testSet_processed), 8))

#Subset only 100 entries for testing
#matrix_data <- matrix_data[1:100, ]
#matrix_targets <- matrix_targets[1:100, ]

Build Model

#train_data <- matrix_data
train_data <- data.matrix(matrix_data)
test_data <- data.matrix(matrix_data_test)
train_targets <- data.matrix(matrix_targets)
test_targets <- data.matrix(matrix_targets_test)

# Function to build the model
build_model <- function() {
  model <- keras_model_sequential() %>%
    #layer_batch_normalization(axis = -1L, input_shape = dim(train_data)[[2]]) %>%
    layer_dense(units = 64, activation = "relu", input_shape = dim(train_data)[[2]]) %>%
    layer_dense(units = 64, activation = "relu") %>%
    #layer_dropout(0.3) %>%
    layer_dense(units = 128, activation = "relu") %>%
    layer_dense(units = 128, activation = "relu") %>%
    layer_dense(units = 64, activation = "relu") %>%
    layer_dense(units = 64, activation = "relu") %>%
    layer_dense(units = 8, activation = "softmax") 

  model %>% compile(
    optimizer = optimizer_sgd(learning_rate = 0.2),
    loss = "categorical_crossentropy",
    metrics = "categorical_accuracy"
  )

}

K-Fold-Validation

k <- 10
indices <- sample(1:nrow(train_data))
folds <- cut(indices, breaks = k, labels = FALSE)

num_epochs <- 250
all_acc_histories <- NULL
for (i in 1:k) {
  cat("processing fold #", i, "\n")

  val_indices <- which(folds == i, arr.ind = TRUE)
  val_data <- train_data[val_indices,] #test_data#
  val_targets <- train_targets[val_indices,] #test_targets#
  
  partial_train_data <- train_data[-val_indices,]
  partial_train_targets <- train_targets[-val_indices,]
  model <- build_model()

  # Train the model (in silent mode, verbose=0)
  # Batch size https://stats.stackexchange.com/questions/153531/what-is-batch-size-in-neural-network
  # One epoch = one forward pass and one backward pass of all the training examples
  # Batch size = the number of training examples in one forward/backward pass. The higher the batch size, the more memory space you'll need.
  # Number of iterations = number of passes, each pass using [batch size] number of examples. To be clear, one pass = one forward pass + one backward pass (we do not count the forward pass and backward pass as two different passes).
  # Batch size 32 much faster than 1, also the smaller the batch the less accurate the estimate of the gradient will be.
  history <- model %>% fit(
    partial_train_data, partial_train_targets,
    validation_data = list(val_data, val_targets),
    epochs = num_epochs, batch_size = 2048, verbose = 2#, class_weights = percentage
  )
  acc_history <- history$metrics$val_categorical_accuracy
  all_acc_histories <- rbind(all_acc_histories, acc_history)
}

processing fold # 1 

2022-12-31 11:02:21.507793: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX AVX2
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2022-12-31 11:02:21.863292: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 5484 MB memory:  -> device: 0, name: NVIDIA GeForce RTX 3060 Ti, pci bus id: 0000:2d:00.0, compute capability: 8.6

Epoch 1/250

2022-12-31 11:02:23.049628: I tensorflow/stream_executor/cuda/cuda_blas.cc:1786] TensorFloat-32 will be used for the matrix multiplication. This will only be logged once.

141/141 - 2s - loss: 1.9670 - categorical_accuracy: 0.2569 - val_loss: 2.0312 - val_categorical_accuracy: 0.1870 - 2s/epoch - 15ms/step
Epoch 2/250
141/141 - 1s - loss: 1.6148 - categorical_accuracy: 0.3890 - val_loss: 1.3623 - val_categorical_accuracy: 0.4710 - 714ms/epoch - 5ms/step
Epoch 3/250
141/141 - 1s - loss: 1.3558 - categorical_accuracy: 0.4848 - val_loss: 1.3714 - val_categorical_accuracy: 0.4837 - 686ms/epoch - 5ms/step
Epoch 4/250
141/141 - 1s - loss: 1.2234 - categorical_accuracy: 0.5437 - val_loss: 1.1069 - val_categorical_accuracy: 0.5711 - 667ms/epoch - 5ms/step
Epoch 5/250
141/141 - 1s - loss: 1.0629 - categorical_accuracy: 0.6029 - val_loss: 0.9641 - val_categorical_accuracy: 0.6348 - 669ms/epoch - 5ms/step
Epoch 6/250
141/141 - 1s - loss: 0.9428 - categorical_accuracy: 0.6483 - val_loss: 0.8593 - val_categorical_accuracy: 0.6850 - 668ms/epoch - 5ms/step
Epoch 7/250
141/141 - 1s - loss: 0.8499 - categorical_accuracy: 0.6828 - val_loss: 0.7943 - val_categorical_accuracy: 0.6959 - 651ms/epoch - 5ms/step
Epoch 8/250
141/141 - 1s - loss: 0.7906 - categorical_accuracy: 0.7074 - val_loss: 0.8104 - val_categorical_accuracy: 0.6864 - 768ms/epoch - 5ms/step
Epoch 9/250
141/141 - 1s - loss: 0.7953 - categorical_accuracy: 0.7117 - val_loss: 0.7729 - val_categorical_accuracy: 0.7050 - 844ms/epoch - 6ms/step
Epoch 10/250
141/141 - 1s - loss: 0.6679 - categorical_accuracy: 0.7502 - val_loss: 0.6231 - val_categorical_accuracy: 0.7652 - 871ms/epoch - 6ms/step
Epoch 11/250
141/141 - 1s - loss: 0.6368 - categorical_accuracy: 0.7624 - val_loss: 0.6008 - val_categorical_accuracy: 0.7768 - 924ms/epoch - 7ms/step
Epoch 12/250
141/141 - 1s - loss: 0.5999 - categorical_accuracy: 0.7766 - val_loss: 0.5308 - val_categorical_accuracy: 0.8021 - 877ms/epoch - 6ms/step
Epoch 13/250
141/141 - 1s - loss: 0.6283 - categorical_accuracy: 0.7740 - val_loss: 0.5804 - val_categorical_accuracy: 0.7770 - 894ms/epoch - 6ms/step
Epoch 14/250
141/141 - 1s - loss: 0.5489 - categorical_accuracy: 0.7977 - val_loss: 0.5124 - val_categorical_accuracy: 0.8126 - 890ms/epoch - 6ms/step
Epoch 15/250
141/141 - 1s - loss: 0.5333 - categorical_accuracy: 0.8042 - val_loss: 0.4781 - val_categorical_accuracy: 0.8263 - 893ms/epoch - 6ms/step
Epoch 16/250
141/141 - 1s - loss: 0.5133 - categorical_accuracy: 0.8131 - val_loss: 0.5099 - val_categorical_accuracy: 0.8039 - 894ms/epoch - 6ms/step
Epoch 17/250
141/141 - 1s - loss: 0.4593 - categorical_accuracy: 0.8291 - val_loss: 0.6640 - val_categorical_accuracy: 0.7722 - 878ms/epoch - 6ms/step
Epoch 18/250
141/141 - 1s - loss: 0.5594 - categorical_accuracy: 0.8059 - val_loss: 0.4218 - val_categorical_accuracy: 0.8431 - 888ms/epoch - 6ms/step
Epoch 19/250
141/141 - 1s - loss: 0.4349 - categorical_accuracy: 0.8400 - val_loss: 0.5271 - val_categorical_accuracy: 0.8043 - 871ms/epoch - 6ms/step
Epoch 20/250
141/141 - 1s - loss: 0.4317 - categorical_accuracy: 0.8430 - val_loss: 0.4177 - val_categorical_accuracy: 0.8387 - 876ms/epoch - 6ms/step
Epoch 21/250
141/141 - 1s - loss: 0.4269 - categorical_accuracy: 0.8458 - val_loss: 0.4105 - val_categorical_accuracy: 0.8495 - 862ms/epoch - 6ms/step
Epoch 22/250
141/141 - 1s - loss: 0.3855 - categorical_accuracy: 0.8588 - val_loss: 0.3569 - val_categorical_accuracy: 0.8721 - 878ms/epoch - 6ms/step
Epoch 23/250
141/141 - 1s - loss: 0.4033 - categorical_accuracy: 0.8550 - val_loss: 0.4634 - val_categorical_accuracy: 0.8309 - 859ms/epoch - 6ms/step
Epoch 24/250
141/141 - 1s - loss: 0.5657 - categorical_accuracy: 0.8137 - val_loss: 0.4507 - val_categorical_accuracy: 0.8368 - 879ms/epoch - 6ms/step
Epoch 25/250
141/141 - 1s - loss: 0.3649 - categorical_accuracy: 0.8688 - val_loss: 0.3970 - val_categorical_accuracy: 0.8534 - 893ms/epoch - 6ms/step
Epoch 26/250
141/141 - 1s - loss: 0.3561 - categorical_accuracy: 0.8712 - val_loss: 0.3271 - val_categorical_accuracy: 0.8839 - 891ms/epoch - 6ms/step
Epoch 27/250
141/141 - 1s - loss: 0.3441 - categorical_accuracy: 0.8761 - val_loss: 0.3423 - val_categorical_accuracy: 0.8776 - 859ms/epoch - 6ms/step
Epoch 28/250
141/141 - 1s - loss: 0.3255 - categorical_accuracy: 0.8836 - val_loss: 0.3521 - val_categorical_accuracy: 0.8663 - 888ms/epoch - 6ms/step
Epoch 29/250
141/141 - 1s - loss: 0.3358 - categorical_accuracy: 0.8817 - val_loss: 0.3865 - val_categorical_accuracy: 0.8562 - 893ms/epoch - 6ms/step
Epoch 30/250
141/141 - 1s - loss: 0.3124 - categorical_accuracy: 0.8876 - val_loss: 0.2999 - val_categorical_accuracy: 0.8920 - 876ms/epoch - 6ms/step
Epoch 31/250
141/141 - 1s - loss: 0.3052 - categorical_accuracy: 0.8902 - val_loss: 0.3621 - val_categorical_accuracy: 0.8673 - 874ms/epoch - 6ms/step
Epoch 32/250
141/141 - 1s - loss: 0.2899 - categorical_accuracy: 0.8961 - val_loss: 0.3759 - val_categorical_accuracy: 0.8692 - 877ms/epoch - 6ms/step
Epoch 33/250
141/141 - 1s - loss: 0.2845 - categorical_accuracy: 0.8977 - val_loss: 0.2810 - val_categorical_accuracy: 0.8996 - 890ms/epoch - 6ms/step
Epoch 34/250
141/141 - 1s - loss: 0.7452 - categorical_accuracy: 0.7639 - val_loss: 0.3894 - val_categorical_accuracy: 0.8607 - 859ms/epoch - 6ms/step
Epoch 35/250
141/141 - 1s - loss: 0.3382 - categorical_accuracy: 0.8796 - val_loss: 0.3116 - val_categorical_accuracy: 0.8884 - 863ms/epoch - 6ms/step
Epoch 36/250
141/141 - 1s - loss: 0.3102 - categorical_accuracy: 0.8918 - val_loss: 0.3307 - val_categorical_accuracy: 0.8822 - 894ms/epoch - 6ms/step
Epoch 37/250
141/141 - 1s - loss: 0.2852 - categorical_accuracy: 0.8991 - val_loss: 0.3496 - val_categorical_accuracy: 0.8697 - 876ms/epoch - 6ms/step
Epoch 38/250
141/141 - 1s - loss: 0.2724 - categorical_accuracy: 0.9030 - val_loss: 0.2605 - val_categorical_accuracy: 0.9075 - 860ms/epoch - 6ms/step
Epoch 39/250
141/141 - 1s - loss: 0.2660 - categorical_accuracy: 0.9061 - val_loss: 0.3402 - val_categorical_accuracy: 0.8753 - 856ms/epoch - 6ms/step
Epoch 40/250
141/141 - 1s - loss: 0.2587 - categorical_accuracy: 0.9082 - val_loss: 0.3116 - val_categorical_accuracy: 0.8875 - 878ms/epoch - 6ms/step
Epoch 41/250
141/141 - 1s - loss: 0.2441 - categorical_accuracy: 0.9130 - val_loss: 0.2584 - val_categorical_accuracy: 0.9069 - 893ms/epoch - 6ms/step
Epoch 42/250
141/141 - 1s - loss: 0.2444 - categorical_accuracy: 0.9131 - val_loss: 0.3109 - val_categorical_accuracy: 0.8871 - 908ms/epoch - 6ms/step
Epoch 43/250
141/141 - 1s - loss: 0.2607 - categorical_accuracy: 0.9101 - val_loss: 0.4341 - val_categorical_accuracy: 0.8454 - 875ms/epoch - 6ms/step
Epoch 44/250
141/141 - 1s - loss: 0.2306 - categorical_accuracy: 0.9190 - val_loss: 0.2486 - val_categorical_accuracy: 0.9134 - 895ms/epoch - 6ms/step
Epoch 45/250
141/141 - 1s - loss: 0.3154 - categorical_accuracy: 0.8977 - val_loss: 0.3265 - val_categorical_accuracy: 0.8889 - 876ms/epoch - 6ms/step
Epoch 46/250
141/141 - 1s - loss: 0.2256 - categorical_accuracy: 0.9217 - val_loss: 0.2737 - val_categorical_accuracy: 0.9030 - 872ms/epoch - 6ms/step
Epoch 47/250
141/141 - 1s - loss: 0.2147 - categorical_accuracy: 0.9248 - val_loss: 0.2470 - val_categorical_accuracy: 0.9094 - 875ms/epoch - 6ms/step
Epoch 48/250
141/141 - 1s - loss: 0.2974 - categorical_accuracy: 0.9041 - val_loss: 0.2337 - val_categorical_accuracy: 0.9179 - 892ms/epoch - 6ms/step
Epoch 49/250
141/141 - 1s - loss: 0.2079 - categorical_accuracy: 0.9273 - val_loss: 0.2255 - val_categorical_accuracy: 0.9207 - 874ms/epoch - 6ms/step
Epoch 50/250
141/141 - 1s - loss: 0.2100 - categorical_accuracy: 0.9262 - val_loss: 0.2168 - val_categorical_accuracy: 0.9255 - 875ms/epoch - 6ms/step
Epoch 51/250
141/141 - 1s - loss: 0.2256 - categorical_accuracy: 0.9227 - val_loss: 0.2414 - val_categorical_accuracy: 0.9131 - 878ms/epoch - 6ms/step
Epoch 52/250
141/141 - 1s - loss: 0.2021 - categorical_accuracy: 0.9292 - val_loss: 0.2194 - val_categorical_accuracy: 0.9235 - 876ms/epoch - 6ms/step
Epoch 53/250
141/141 - 1s - loss: 0.2093 - categorical_accuracy: 0.9277 - val_loss: 0.2148 - val_categorical_accuracy: 0.9257 - 890ms/epoch - 6ms/step
Epoch 54/250
141/141 - 1s - loss: 0.1927 - categorical_accuracy: 0.9325 - val_loss: 0.2293 - val_categorical_accuracy: 0.9217 - 894ms/epoch - 6ms/step
Epoch 55/250
Epoch 56/250
141/141 - 1s - loss: 0.2156 - categorical_accuracy: 0.9267 - val_loss: 0.2246 - val_categorical_accuracy: 0.9227 - 894ms/epoch - 6ms/step
Epoch 57/250
141/141 - 1s - loss: 0.1995 - categorical_accuracy: 0.9311 - val_loss: 0.2142 - val_categorical_accuracy: 0.9260 - 878ms/epoch - 6ms/step
Epoch 58/250
141/141 - 1s - loss: 0.1839 - categorical_accuracy: 0.9356 - val_loss: 0.2426 - val_categorical_accuracy: 0.9122 - 892ms/epoch - 6ms/step
Epoch 59/250
141/141 - 1s - loss: 0.1878 - categorical_accuracy: 0.9346 - val_loss: 0.2093 - val_categorical_accuracy: 0.9282 - 877ms/epoch - 6ms/step
Epoch 60/250
141/141 - 1s - loss: 0.2110 - categorical_accuracy: 0.9313 - val_loss: 0.2843 - val_categorical_accuracy: 0.9004 - 891ms/epoch - 6ms/step
Epoch 61/250
141/141 - 1s - loss: 0.1851 - categorical_accuracy: 0.9352 - val_loss: 0.2112 - val_categorical_accuracy: 0.9261 - 891ms/epoch - 6ms/step
Epoch 62/250
141/141 - 1s - loss: 0.1799 - categorical_accuracy: 0.9379 - val_loss: 0.2217 - val_categorical_accuracy: 0.9195 - 874ms/epoch - 6ms/step
Epoch 63/250
141/141 - 1s - loss: 0.1813 - categorical_accuracy: 0.9367 - val_loss: 0.3008 - val_categorical_accuracy: 0.8936 - 862ms/epoch - 6ms/step
Epoch 64/250
141/141 - 1s - loss: 0.1762 - categorical_accuracy: 0.9385 - val_loss: 0.2054 - val_categorical_accuracy: 0.9293 - 859ms/epoch - 6ms/step
Epoch 65/250
141/141 - 1s - loss: 0.1758 - categorical_accuracy: 0.9390 - val_loss: 0.1970 - val_categorical_accuracy: 0.9323 - 889ms/epoch - 6ms/step
Epoch 66/250
141/141 - 1s - loss: 0.1773 - categorical_accuracy: 0.9396 - val_loss: 0.2054 - val_categorical_accuracy: 0.9313 - 877ms/epoch - 6ms/step
Epoch 67/250
141/141 - 1s - loss: 0.1682 - categorical_accuracy: 0.9417 - val_loss: 0.2053 - val_categorical_accuracy: 0.9291 - 880ms/epoch - 6ms/step
Epoch 68/250
141/141 - 1s - loss: 0.1709 - categorical_accuracy: 0.9408 - val_loss: 0.1966 - val_categorical_accuracy: 0.9344 - 887ms/epoch - 6ms/step
Epoch 69/250
141/141 - 1s - loss: 0.1653 - categorical_accuracy: 0.9425 - val_loss: 0.1921 - val_categorical_accuracy: 0.9340 - 890ms/epoch - 6ms/step
Epoch 70/250
141/141 - 1s - loss: 0.3702 - categorical_accuracy: 0.8890 - val_loss: 0.2216 - val_categorical_accuracy: 0.9228 - 878ms/epoch - 6ms/step
Epoch 71/250
141/141 - 1s - loss: 0.1749 - categorical_accuracy: 0.9407 - val_loss: 0.2029 - val_categorical_accuracy: 0.9310 - 847ms/epoch - 6ms/step
Epoch 72/250
141/141 - 1s - loss: 0.1511 - categorical_accuracy: 0.9485 - val_loss: 0.1763 - val_categorical_accuracy: 0.9403 - 878ms/epoch - 6ms/step
Epoch 73/250
141/141 - 1s - loss: 0.1715 - categorical_accuracy: 0.9427 - val_loss: 0.1938 - val_categorical_accuracy: 0.9340 - 873ms/epoch - 6ms/step
Epoch 74/250
141/141 - 1s - loss: 0.1630 - categorical_accuracy: 0.9440 - val_loss: 0.1986 - val_categorical_accuracy: 0.9325 - 875ms/epoch - 6ms/step
Epoch 75/250
141/141 - 1s - loss: 0.1453 - categorical_accuracy: 0.9500 - val_loss: 0.1854 - val_categorical_accuracy: 0.9362 - 859ms/epoch - 6ms/step
Epoch 76/250
141/141 - 1s - loss: 0.1511 - categorical_accuracy: 0.9476 - val_loss: 0.1743 - val_categorical_accuracy: 0.9410 - 889ms/epoch - 6ms/step
Epoch 77/250
141/141 - 1s - loss: 0.8783 - categorical_accuracy: 0.7292 - val_loss: 0.3600 - val_categorical_accuracy: 0.8708 - 894ms/epoch - 6ms/step
Epoch 78/250
141/141 - 1s - loss: 0.2531 - categorical_accuracy: 0.9116 - val_loss: 0.2308 - val_categorical_accuracy: 0.9190 - 875ms/epoch - 6ms/step
Epoch 79/250
141/141 - 1s - loss: 0.1936 - categorical_accuracy: 0.9327 - val_loss: 0.2166 - val_categorical_accuracy: 0.9240 - 876ms/epoch - 6ms/step
Epoch 80/250
141/141 - 1s - loss: 0.1757 - categorical_accuracy: 0.9394 - val_loss: 0.2288 - val_categorical_accuracy: 0.9197 - 876ms/epoch - 6ms/step
Epoch 81/250
141/141 - 1s - loss: 0.1718 - categorical_accuracy: 0.9406 - val_loss: 0.2071 - val_categorical_accuracy: 0.9297 - 909ms/epoch - 6ms/step
Epoch 82/250
141/141 - 1s - loss: 0.1635 - categorical_accuracy: 0.9442 - val_loss: 0.1970 - val_categorical_accuracy: 0.9342 - 909ms/epoch - 6ms/step
Epoch 83/250
141/141 - 1s - loss: 0.1498 - categorical_accuracy: 0.9485 - val_loss: 0.2106 - val_categorical_accuracy: 0.9276 - 875ms/epoch - 6ms/step
Epoch 84/250
141/141 - 1s - loss: 0.1766 - categorical_accuracy: 0.9417 - val_loss: 0.1878 - val_categorical_accuracy: 0.9334 - 891ms/epoch - 6ms/step
Epoch 85/250
141/141 - 1s - loss: 0.1422 - categorical_accuracy: 0.9514 - val_loss: 0.2504 - val_categorical_accuracy: 0.9131 - 902ms/epoch - 6ms/step
Epoch 86/250
141/141 - 1s - loss: 0.1445 - categorical_accuracy: 0.9504 - val_loss: 0.1881 - val_categorical_accuracy: 0.9352 - 890ms/epoch - 6ms/step
Epoch 87/250
141/141 - 1s - loss: 0.1411 - categorical_accuracy: 0.9514 - val_loss: 0.1997 - val_categorical_accuracy: 0.9343 - 858ms/epoch - 6ms/step
Epoch 88/250
141/141 - 1s - loss: 0.1797 - categorical_accuracy: 0.9426 - val_loss: 0.1820 - val_categorical_accuracy: 0.9374 - 877ms/epoch - 6ms/step
Epoch 89/250
141/141 - 1s - loss: 0.1435 - categorical_accuracy: 0.9515 - val_loss: 0.1901 - val_categorical_accuracy: 0.9375 - 874ms/epoch - 6ms/step
Epoch 90/250
141/141 - 1s - loss: 0.1387 - categorical_accuracy: 0.9527 - val_loss: 0.1724 - val_categorical_accuracy: 0.9437 - 886ms/epoch - 6ms/step
Epoch 91/250
141/141 - 1s - loss: 0.4108 - categorical_accuracy: 0.8773 - val_loss: 0.2505 - val_categorical_accuracy: 0.9156 - 840ms/epoch - 6ms/step
Epoch 92/250
141/141 - 1s - loss: 0.1596 - categorical_accuracy: 0.9456 - val_loss: 0.1783 - val_categorical_accuracy: 0.9415 - 861ms/epoch - 6ms/step
Epoch 93/250
141/141 - 1s - loss: 0.1382 - categorical_accuracy: 0.9527 - val_loss: 0.2198 - val_categorical_accuracy: 0.9233 - 862ms/epoch - 6ms/step
Epoch 94/250
141/141 - 1s - loss: 0.1336 - categorical_accuracy: 0.9541 - val_loss: 0.1671 - val_categorical_accuracy: 0.9447 - 874ms/epoch - 6ms/step
Epoch 95/250
141/141 - 1s - loss: 0.1375 - categorical_accuracy: 0.9525 - val_loss: 0.1732 - val_categorical_accuracy: 0.9431 - 857ms/epoch - 6ms/step
Epoch 96/250
141/141 - 1s - loss: 0.1259 - categorical_accuracy: 0.9568 - val_loss: 0.2084 - val_categorical_accuracy: 0.9326 - 861ms/epoch - 6ms/step
Epoch 97/250
141/141 - 1s - loss: 0.1223 - categorical_accuracy: 0.9578 - val_loss: 0.2145 - val_categorical_accuracy: 0.9323 - 863ms/epoch - 6ms/step
Epoch 98/250
141/141 - 1s - loss: 0.1363 - categorical_accuracy: 0.9539 - val_loss: 0.1771 - val_categorical_accuracy: 0.9396 - 858ms/epoch - 6ms/step
Epoch 99/250
141/141 - 1s - loss: 0.1263 - categorical_accuracy: 0.9569 - val_loss: 0.1785 - val_categorical_accuracy: 0.9382 - 845ms/epoch - 6ms/step
Epoch 100/250
141/141 - 1s - loss: 0.1674 - categorical_accuracy: 0.9470 - val_loss: 0.1736 - val_categorical_accuracy: 0.9414 - 858ms/epoch - 6ms/step
Epoch 101/250
141/141 - 1s - loss: 0.1246 - categorical_accuracy: 0.9577 - val_loss: 0.1693 - val_categorical_accuracy: 0.9446 - 875ms/epoch - 6ms/step
Epoch 102/250
141/141 - 1s - loss: 0.1272 - categorical_accuracy: 0.9562 - val_loss: 0.2221 - val_categorical_accuracy: 0.9217 - 861ms/epoch - 6ms/step
Epoch 103/250
141/141 - 1s - loss: 0.1190 - categorical_accuracy: 0.9591 - val_loss: 0.1855 - val_categorical_accuracy: 0.9387 - 829ms/epoch - 6ms/step
Epoch 104/250
141/141 - 1s - loss: 0.1156 - categorical_accuracy: 0.9602 - val_loss: 0.2158 - val_categorical_accuracy: 0.9315 - 860ms/epoch - 6ms/step
Epoch 105/250
141/141 - 1s - loss: 0.1159 - categorical_accuracy: 0.9605 - val_loss: 0.2175 - val_categorical_accuracy: 0.9304 - 874ms/epoch - 6ms/step
Epoch 106/250
141/141 - 1s - loss: 0.1169 - categorical_accuracy: 0.9603 - val_loss: 0.2194 - val_categorical_accuracy: 0.9239 - 860ms/epoch - 6ms/step
Epoch 107/250
141/141 - 1s - loss: 0.1439 - categorical_accuracy: 0.9526 - val_loss: 0.1630 - val_categorical_accuracy: 0.9461 - 845ms/epoch - 6ms/step
Epoch 108/250
141/141 - 1s - loss: 0.1592 - categorical_accuracy: 0.9503 - val_loss: 0.1813 - val_categorical_accuracy: 0.9381 - 874ms/epoch - 6ms/step
Epoch 109/250
141/141 - 1s - loss: 0.1089 - categorical_accuracy: 0.9634 - val_loss: 0.1694 - val_categorical_accuracy: 0.9413 - 862ms/epoch - 6ms/step
Epoch 110/250
141/141 - 1s - loss: 0.1116 - categorical_accuracy: 0.9619 - val_loss: 0.2479 - val_categorical_accuracy: 0.9165 - 860ms/epoch - 6ms/step
Epoch 111/250
141/141 - 1s - loss: 0.1454 - categorical_accuracy: 0.9523 - val_loss: 0.1722 - val_categorical_accuracy: 0.9421 - 860ms/epoch - 6ms/step
Epoch 112/250
141/141 - 1s - loss: 0.1092 - categorical_accuracy: 0.9628 - val_loss: 0.1648 - val_categorical_accuracy: 0.9446 - 878ms/epoch - 6ms/step
Epoch 113/250
141/141 - 1s - loss: 0.1146 - categorical_accuracy: 0.9610 - val_loss: 0.1650 - val_categorical_accuracy: 0.9465 - 861ms/epoch - 6ms/step
Epoch 114/250
141/141 - 1s - loss: 0.1416 - categorical_accuracy: 0.9544 - val_loss: 0.1927 - val_categorical_accuracy: 0.9355 - 861ms/epoch - 6ms/step
Epoch 115/250
141/141 - 1s - loss: 0.1065 - categorical_accuracy: 0.9641 - val_loss: 0.1566 - val_categorical_accuracy: 0.9484 - 844ms/epoch - 6ms/step
Epoch 116/250
141/141 - 1s - loss: 0.1237 - categorical_accuracy: 0.9586 - val_loss: 0.1570 - val_categorical_accuracy: 0.9485 - 891ms/epoch - 6ms/step
Epoch 117/250
141/141 - 1s - loss: 0.1009 - categorical_accuracy: 0.9656 - val_loss: 0.1679 - val_categorical_accuracy: 0.9427 - 861ms/epoch - 6ms/step
Epoch 118/250
141/141 - 1s - loss: 0.1339 - categorical_accuracy: 0.9567 - val_loss: 0.1814 - val_categorical_accuracy: 0.9436 - 844ms/epoch - 6ms/step
Epoch 119/250
141/141 - 1s - loss: 0.1279 - categorical_accuracy: 0.9584 - val_loss: 0.1719 - val_categorical_accuracy: 0.9446 - 845ms/epoch - 6ms/step
Epoch 120/250
141/141 - 1s - loss: 0.1033 - categorical_accuracy: 0.9648 - val_loss: 0.1803 - val_categorical_accuracy: 0.9400 - 876ms/epoch - 6ms/step
Epoch 121/250
141/141 - 1s - loss: 0.1080 - categorical_accuracy: 0.9633 - val_loss: 0.1958 - val_categorical_accuracy: 0.9385 - 846ms/epoch - 6ms/step
Epoch 122/250
141/141 - 1s - loss: 0.1261 - categorical_accuracy: 0.9584 - val_loss: 0.2078 - val_categorical_accuracy: 0.9361 - 861ms/epoch - 6ms/step
Epoch 123/250
141/141 - 1s - loss: 0.1018 - categorical_accuracy: 0.9650 - val_loss: 0.1548 - val_categorical_accuracy: 0.9504 - 859ms/epoch - 6ms/step
Epoch 124/250
141/141 - 1s - loss: 0.1178 - categorical_accuracy: 0.9612 - val_loss: 0.1636 - val_categorical_accuracy: 0.9455 - 862ms/epoch - 6ms/step
Epoch 125/250
141/141 - 1s - loss: 0.0976 - categorical_accuracy: 0.9668 - val_loss: 0.1671 - val_categorical_accuracy: 0.9459 - 861ms/epoch - 6ms/step
Epoch 126/250
141/141 - 1s - loss: 0.1148 - categorical_accuracy: 0.9619 - val_loss: 0.1576 - val_categorical_accuracy: 0.9477 - 858ms/epoch - 6ms/step
Epoch 127/250
141/141 - 1s - loss: 0.0952 - categorical_accuracy: 0.9677 - val_loss: 0.1599 - val_categorical_accuracy: 0.9485 - 862ms/epoch - 6ms/step
Epoch 128/250
141/141 - 1s - loss: 0.1226 - categorical_accuracy: 0.9598 - val_loss: 0.1536 - val_categorical_accuracy: 0.9488 - 862ms/epoch - 6ms/step
Epoch 129/250
141/141 - 1s - loss: 0.1018 - categorical_accuracy: 0.9650 - val_loss: 0.2085 - val_categorical_accuracy: 0.9343 - 844ms/epoch - 6ms/step
Epoch 130/250
141/141 - 1s - loss: 0.1319 - categorical_accuracy: 0.9588 - val_loss: 0.1730 - val_categorical_accuracy: 0.9425 - 862ms/epoch - 6ms/step
Epoch 131/250
141/141 - 1s - loss: 0.0957 - categorical_accuracy: 0.9680 - val_loss: 0.1769 - val_categorical_accuracy: 0.9421 - 856ms/epoch - 6ms/step
Epoch 132/250
141/141 - 1s - loss: 0.0927 - categorical_accuracy: 0.9685 - val_loss: 0.1685 - val_categorical_accuracy: 0.9458 - 842ms/epoch - 6ms/step
Epoch 133/250
141/141 - 1s - loss: 0.0959 - categorical_accuracy: 0.9672 - val_loss: 0.1556 - val_categorical_accuracy: 0.9501 - 853ms/epoch - 6ms/step
Epoch 134/250
141/141 - 1s - loss: 0.2054 - categorical_accuracy: 0.9396 - val_loss: 0.1593 - val_categorical_accuracy: 0.9473 - 857ms/epoch - 6ms/step
Epoch 135/250
141/141 - 1s - loss: 0.0940 - categorical_accuracy: 0.9683 - val_loss: 0.1587 - val_categorical_accuracy: 0.9494 - 845ms/epoch - 6ms/step
Epoch 136/250
141/141 - 1s - loss: 0.0991 - categorical_accuracy: 0.9665 - val_loss: 0.1559 - val_categorical_accuracy: 0.9498 - 861ms/epoch - 6ms/step
Epoch 137/250
141/141 - 1s - loss: 0.0915 - categorical_accuracy: 0.9688 - val_loss: 0.1738 - val_categorical_accuracy: 0.9451 - 878ms/epoch - 6ms/step
Epoch 138/250
141/141 - 1s - loss: 0.1202 - categorical_accuracy: 0.9615 - val_loss: 0.1508 - val_categorical_accuracy: 0.9520 - 891ms/epoch - 6ms/step
Epoch 139/250
141/141 - 1s - loss: 0.0898 - categorical_accuracy: 0.9695 - val_loss: 0.1759 - val_categorical_accuracy: 0.9410 - 840ms/epoch - 6ms/step
Epoch 140/250
141/141 - 1s - loss: 0.1157 - categorical_accuracy: 0.9625 - val_loss: 0.1706 - val_categorical_accuracy: 0.9433 - 830ms/epoch - 6ms/step
Epoch 141/250
141/141 - 1s - loss: 0.0888 - categorical_accuracy: 0.9698 - val_loss: 0.1599 - val_categorical_accuracy: 0.9495 - 858ms/epoch - 6ms/step
Epoch 142/250
141/141 - 1s - loss: 0.0882 - categorical_accuracy: 0.9698 - val_loss: 0.1883 - val_categorical_accuracy: 0.9421 - 860ms/epoch - 6ms/step
Epoch 143/250
141/141 - 1s - loss: 0.0958 - categorical_accuracy: 0.9675 - val_loss: 0.1939 - val_categorical_accuracy: 0.9394 - 861ms/epoch - 6ms/step
Epoch 144/250
141/141 - 1s - loss: 0.1330 - categorical_accuracy: 0.9587 - val_loss: 0.1750 - val_categorical_accuracy: 0.9448 - 844ms/epoch - 6ms/step
Epoch 145/250
141/141 - 1s - loss: 0.0883 - categorical_accuracy: 0.9699 - val_loss: 0.1475 - val_categorical_accuracy: 0.9540 - 874ms/epoch - 6ms/step
Epoch 146/250
141/141 - 1s - loss: 0.0918 - categorical_accuracy: 0.9688 - val_loss: 0.1621 - val_categorical_accuracy: 0.9491 - 860ms/epoch - 6ms/step
Epoch 147/250
141/141 - 1s - loss: 0.1067 - categorical_accuracy: 0.9653 - val_loss: 0.1579 - val_categorical_accuracy: 0.9476 - 845ms/epoch - 6ms/step
Epoch 148/250
141/141 - 1s - loss: 0.0864 - categorical_accuracy: 0.9704 - val_loss: 0.1534 - val_categorical_accuracy: 0.9514 - 843ms/epoch - 6ms/step
Epoch 149/250
141/141 - 1s - loss: 0.0833 - categorical_accuracy: 0.9717 - val_loss: 0.1685 - val_categorical_accuracy: 0.9487 - 889ms/epoch - 6ms/step
Epoch 150/250
141/141 - 1s - loss: 0.1126 - categorical_accuracy: 0.9637 - val_loss: 0.1547 - val_categorical_accuracy: 0.9531 - 879ms/epoch - 6ms/step
Epoch 151/250
141/141 - 1s - loss: 0.0815 - categorical_accuracy: 0.9722 - val_loss: 0.1604 - val_categorical_accuracy: 0.9490 - 878ms/epoch - 6ms/step
Epoch 152/250
141/141 - 1s - loss: 0.0871 - categorical_accuracy: 0.9702 - val_loss: 0.1454 - val_categorical_accuracy: 0.9536 - 858ms/epoch - 6ms/step
Epoch 153/250
141/141 - 1s - loss: 0.1538 - categorical_accuracy: 0.9546 - val_loss: 0.2245 - val_categorical_accuracy: 0.9227 - 857ms/epoch - 6ms/step
Epoch 154/250
141/141 - 1s - loss: 0.0912 - categorical_accuracy: 0.9695 - val_loss: 0.1603 - val_categorical_accuracy: 0.9502 - 844ms/epoch - 6ms/step
Epoch 155/250
141/141 - 1s - loss: 0.1034 - categorical_accuracy: 0.9662 - val_loss: 0.1605 - val_categorical_accuracy: 0.9482 - 859ms/epoch - 6ms/step
Epoch 156/250
141/141 - 1s - loss: 0.0839 - categorical_accuracy: 0.9715 - val_loss: 0.1985 - val_categorical_accuracy: 0.9338 - 860ms/epoch - 6ms/step
Epoch 157/250
141/141 - 1s - loss: 0.0853 - categorical_accuracy: 0.9710 - val_loss: 0.2122 - val_categorical_accuracy: 0.9349 - 862ms/epoch - 6ms/step
Epoch 158/250
141/141 - 1s - loss: 0.1488 - categorical_accuracy: 0.9553 - val_loss: 0.1622 - val_categorical_accuracy: 0.9466 - 861ms/epoch - 6ms/step
Epoch 159/250
141/141 - 1s - loss: 0.0819 - categorical_accuracy: 0.9725 - val_loss: 0.2039 - val_categorical_accuracy: 0.9385 - 859ms/epoch - 6ms/step
Epoch 160/250
141/141 - 1s - loss: 0.0811 - categorical_accuracy: 0.9726 - val_loss: 0.1557 - val_categorical_accuracy: 0.9529 - 861ms/epoch - 6ms/step
Epoch 161/250
141/141 - 1s - loss: 0.0825 - categorical_accuracy: 0.9715 - val_loss: 0.2360 - val_categorical_accuracy: 0.9210 - 845ms/epoch - 6ms/step
Epoch 162/250
141/141 - 1s - loss: 0.0830 - categorical_accuracy: 0.9719 - val_loss: 0.1611 - val_categorical_accuracy: 0.9488 - 846ms/epoch - 6ms/step
Epoch 163/250
141/141 - 1s - loss: 0.1211 - categorical_accuracy: 0.9622 - val_loss: 0.1624 - val_categorical_accuracy: 0.9476 - 862ms/epoch - 6ms/step
Epoch 164/250
141/141 - 1s - loss: 0.0791 - categorical_accuracy: 0.9731 - val_loss: 0.2006 - val_categorical_accuracy: 0.9417 - 862ms/epoch - 6ms/step
Epoch 165/250
141/141 - 1s - loss: 0.1077 - categorical_accuracy: 0.9659 - val_loss: 0.1602 - val_categorical_accuracy: 0.9508 - 863ms/epoch - 6ms/step
Epoch 166/250
141/141 - 1s - loss: 0.0873 - categorical_accuracy: 0.9706 - val_loss: 0.1545 - val_categorical_accuracy: 0.9532 - 874ms/epoch - 6ms/step
Epoch 167/250
141/141 - 1s - loss: 0.0979 - categorical_accuracy: 0.9679 - val_loss: 0.1493 - val_categorical_accuracy: 0.9543 - 861ms/epoch - 6ms/step
Epoch 168/250
141/141 - 1s - loss: 0.0771 - categorical_accuracy: 0.9740 - val_loss: 0.1584 - val_categorical_accuracy: 0.9488 - 859ms/epoch - 6ms/step
Epoch 169/250
141/141 - 1s - loss: 0.0850 - categorical_accuracy: 0.9713 - val_loss: 0.1494 - val_categorical_accuracy: 0.9528 - 827ms/epoch - 6ms/step
Epoch 170/250
141/141 - 1s - loss: 0.0761 - categorical_accuracy: 0.9740 - val_loss: 0.1592 - val_categorical_accuracy: 0.9523 - 861ms/epoch - 6ms/step
Epoch 171/250
141/141 - 1s - loss: 0.0888 - categorical_accuracy: 0.9699 - val_loss: 0.1660 - val_categorical_accuracy: 0.9498 - 890ms/epoch - 6ms/step
Epoch 172/250
141/141 - 1s - loss: 0.0787 - categorical_accuracy: 0.9731 - val_loss: 0.1610 - val_categorical_accuracy: 0.9514 - 858ms/epoch - 6ms/step
Epoch 173/250
141/141 - 1s - loss: 0.0819 - categorical_accuracy: 0.9718 - val_loss: 0.7359 - val_categorical_accuracy: 0.8378 - 847ms/epoch - 6ms/step
Epoch 174/250
141/141 - 1s - loss: 0.0982 - categorical_accuracy: 0.9687 - val_loss: 0.1910 - val_categorical_accuracy: 0.9427 - 846ms/epoch - 6ms/step
Epoch 175/250
141/141 - 1s - loss: 0.0769 - categorical_accuracy: 0.9733 - val_loss: 0.1586 - val_categorical_accuracy: 0.9509 - 858ms/epoch - 6ms/step
Epoch 176/250
141/141 - 1s - loss: 0.0767 - categorical_accuracy: 0.9740 - val_loss: 0.1553 - val_categorical_accuracy: 0.9534 - 844ms/epoch - 6ms/step
Epoch 177/250
141/141 - 1s - loss: 0.1899 - categorical_accuracy: 0.9452 - val_loss: 0.1523 - val_categorical_accuracy: 0.9524 - 846ms/epoch - 6ms/step
Epoch 178/250
141/141 - 1s - loss: 0.0778 - categorical_accuracy: 0.9736 - val_loss: 0.1564 - val_categorical_accuracy: 0.9535 - 872ms/epoch - 6ms/step
Epoch 179/250
141/141 - 1s - loss: 0.0753 - categorical_accuracy: 0.9745 - val_loss: 0.1636 - val_categorical_accuracy: 0.9504 - 839ms/epoch - 6ms/step
Epoch 180/250
141/141 - 1s - loss: 0.0751 - categorical_accuracy: 0.9746 - val_loss: 0.1610 - val_categorical_accuracy: 0.9495 - 856ms/epoch - 6ms/step
Epoch 181/250
141/141 - 1s - loss: 0.1091 - categorical_accuracy: 0.9644 - val_loss: 0.1646 - val_categorical_accuracy: 0.9508 - 863ms/epoch - 6ms/step
Epoch 182/250
141/141 - 1s - loss: 0.0727 - categorical_accuracy: 0.9756 - val_loss: 0.1552 - val_categorical_accuracy: 0.9543 - 876ms/epoch - 6ms/step
Epoch 183/250
141/141 - 1s - loss: 0.1198 - categorical_accuracy: 0.9635 - val_loss: 0.1574 - val_categorical_accuracy: 0.9490 - 879ms/epoch - 6ms/step
Epoch 184/250
141/141 - 1s - loss: 0.0750 - categorical_accuracy: 0.9747 - val_loss: 0.1773 - val_categorical_accuracy: 0.9430 - 843ms/epoch - 6ms/step
Epoch 185/250
141/141 - 1s - loss: 0.0723 - categorical_accuracy: 0.9755 - val_loss: 0.1990 - val_categorical_accuracy: 0.9384 - 845ms/epoch - 6ms/step
Epoch 186/250
141/141 - 1s - loss: 0.0924 - categorical_accuracy: 0.9704 - val_loss: 0.2085 - val_categorical_accuracy: 0.9443 - 893ms/epoch - 6ms/step
Epoch 187/250
141/141 - 1s - loss: 0.0735 - categorical_accuracy: 0.9752 - val_loss: 0.2280 - val_categorical_accuracy: 0.9270 - 878ms/epoch - 6ms/step
Epoch 188/250
141/141 - 1s - loss: 0.0751 - categorical_accuracy: 0.9745 - val_loss: 0.1465 - val_categorical_accuracy: 0.9547 - 877ms/epoch - 6ms/step
Epoch 189/250
141/141 - 1s - loss: 0.0765 - categorical_accuracy: 0.9737 - val_loss: 0.1748 - val_categorical_accuracy: 0.9490 - 846ms/epoch - 6ms/step
Epoch 190/250
141/141 - 1s - loss: 0.0745 - categorical_accuracy: 0.9744 - val_loss: 0.1623 - val_categorical_accuracy: 0.9530 - 839ms/epoch - 6ms/step
Epoch 191/250
141/141 - 1s - loss: 0.0758 - categorical_accuracy: 0.9742 - val_loss: 0.1684 - val_categorical_accuracy: 0.9504 - 847ms/epoch - 6ms/step
Epoch 192/250
141/141 - 1s - loss: 0.1387 - categorical_accuracy: 0.9577 - val_loss: 0.1620 - val_categorical_accuracy: 0.9506 - 859ms/epoch - 6ms/step
Epoch 193/250
141/141 - 1s - loss: 0.0709 - categorical_accuracy: 0.9761 - val_loss: 0.1475 - val_categorical_accuracy: 0.9576 - 859ms/epoch - 6ms/step
Epoch 194/250
141/141 - 1s - loss: 0.0722 - categorical_accuracy: 0.9754 - val_loss: 0.2296 - val_categorical_accuracy: 0.9355 - 875ms/epoch - 6ms/step
Epoch 195/250
141/141 - 1s - loss: 0.1251 - categorical_accuracy: 0.9630 - val_loss: 0.1627 - val_categorical_accuracy: 0.9524 - 876ms/epoch - 6ms/step
Epoch 196/250
141/141 - 1s - loss: 0.0715 - categorical_accuracy: 0.9755 - val_loss: 0.1562 - val_categorical_accuracy: 0.9551 - 860ms/epoch - 6ms/step
Epoch 197/250
141/141 - 1s - loss: 0.1189 - categorical_accuracy: 0.9644 - val_loss: 0.1486 - val_categorical_accuracy: 0.9556 - 844ms/epoch - 6ms/step
Epoch 198/250
141/141 - 1s - loss: 0.0686 - categorical_accuracy: 0.9770 - val_loss: 0.1681 - val_categorical_accuracy: 0.9498 - 861ms/epoch - 6ms/step
Epoch 199/250
141/141 - 1s - loss: 0.0698 - categorical_accuracy: 0.9763 - val_loss: 0.1536 - val_categorical_accuracy: 0.9558 - 859ms/epoch - 6ms/step
Epoch 200/250
141/141 - 1s - loss: 0.0728 - categorical_accuracy: 0.9751 - val_loss: 0.1598 - val_categorical_accuracy: 0.9517 - 876ms/epoch - 6ms/step
Epoch 201/250
141/141 - 1s - loss: 0.0709 - categorical_accuracy: 0.9761 - val_loss: 0.1730 - val_categorical_accuracy: 0.9482 - 858ms/epoch - 6ms/step
Epoch 202/250
141/141 - 1s - loss: 0.0730 - categorical_accuracy: 0.9749 - val_loss: 0.4145 - val_categorical_accuracy: 0.8854 - 862ms/epoch - 6ms/step
Epoch 203/250
141/141 - 1s - loss: 0.1105 - categorical_accuracy: 0.9664 - val_loss: 0.1894 - val_categorical_accuracy: 0.9396 - 863ms/epoch - 6ms/step
Epoch 204/250
141/141 - 1s - loss: 0.0740 - categorical_accuracy: 0.9748 - val_loss: 0.1445 - val_categorical_accuracy: 0.9564 - 856ms/epoch - 6ms/step
Epoch 205/250
Epoch 206/250
141/141 - 1s - loss: 0.0690 - categorical_accuracy: 0.9764 - val_loss: 0.1513 - val_categorical_accuracy: 0.9544 - 848ms/epoch - 6ms/step
Epoch 207/250
141/141 - 1s - loss: 0.0709 - categorical_accuracy: 0.9756 - val_loss: 0.1568 - val_categorical_accuracy: 0.9529 - 855ms/epoch - 6ms/step
Epoch 208/250
141/141 - 1s - loss: 0.0902 - categorical_accuracy: 0.9710 - val_loss: 0.1693 - val_categorical_accuracy: 0.9482 - 878ms/epoch - 6ms/step
Epoch 209/250
141/141 - 1s - loss: 0.0698 - categorical_accuracy: 0.9761 - val_loss: 0.1449 - val_categorical_accuracy: 0.9570 - 861ms/epoch - 6ms/step
Epoch 210/250
141/141 - 1s - loss: 0.0687 - categorical_accuracy: 0.9767 - val_loss: 0.1826 - val_categorical_accuracy: 0.9508 - 877ms/epoch - 6ms/step
Epoch 211/250
141/141 - 1s - loss: 0.0721 - categorical_accuracy: 0.9753 - val_loss: 0.1614 - val_categorical_accuracy: 0.9541 - 861ms/epoch - 6ms/step
Epoch 212/250
141/141 - 1s - loss: 0.0691 - categorical_accuracy: 0.9762 - val_loss: 0.1566 - val_categorical_accuracy: 0.9540 - 843ms/epoch - 6ms/step
Epoch 213/250
141/141 - 1s - loss: 0.0680 - categorical_accuracy: 0.9764 - val_loss: 0.1593 - val_categorical_accuracy: 0.9534 - 853ms/epoch - 6ms/step
Epoch 214/250
141/141 - 1s - loss: 0.0673 - categorical_accuracy: 0.9769 - val_loss: 0.1900 - val_categorical_accuracy: 0.9425 - 857ms/epoch - 6ms/step
Epoch 215/250
141/141 - 1s - loss: 0.1201 - categorical_accuracy: 0.9641 - val_loss: 0.1537 - val_categorical_accuracy: 0.9531 - 876ms/epoch - 6ms/step
Epoch 216/250
141/141 - 1s - loss: 0.0683 - categorical_accuracy: 0.9768 - val_loss: 0.1746 - val_categorical_accuracy: 0.9476 - 860ms/epoch - 6ms/step
Epoch 217/250
141/141 - 1s - loss: 0.0667 - categorical_accuracy: 0.9772 - val_loss: 0.1843 - val_categorical_accuracy: 0.9483 - 844ms/epoch - 6ms/step
Epoch 218/250
141/141 - 1s - loss: 0.1117 - categorical_accuracy: 0.9664 - val_loss: 0.1730 - val_categorical_accuracy: 0.9463 - 858ms/epoch - 6ms/step
Epoch 219/250
141/141 - 1s - loss: 0.0709 - categorical_accuracy: 0.9759 - val_loss: 0.1530 - val_categorical_accuracy: 0.9559 - 871ms/epoch - 6ms/step
Epoch 220/250
141/141 - 1s - loss: 0.0708 - categorical_accuracy: 0.9758 - val_loss: 0.4005 - val_categorical_accuracy: 0.8970 - 878ms/epoch - 6ms/step
Epoch 221/250
141/141 - 1s - loss: 0.0733 - categorical_accuracy: 0.9753 - val_loss: 0.1693 - val_categorical_accuracy: 0.9538 - 878ms/epoch - 6ms/step
Epoch 222/250
141/141 - 1s - loss: 0.0966 - categorical_accuracy: 0.9702 - val_loss: 0.1495 - val_categorical_accuracy: 0.9565 - 857ms/epoch - 6ms/step
Epoch 223/250
141/141 - 1s - loss: 0.0652 - categorical_accuracy: 0.9777 - val_loss: 0.1479 - val_categorical_accuracy: 0.9568 - 878ms/epoch - 6ms/step
Epoch 224/250
141/141 - 1s - loss: 0.0649 - categorical_accuracy: 0.9777 - val_loss: 0.1874 - val_categorical_accuracy: 0.9478 - 844ms/epoch - 6ms/step
Epoch 225/250
141/141 - 1s - loss: 0.0772 - categorical_accuracy: 0.9740 - val_loss: 0.1537 - val_categorical_accuracy: 0.9564 - 845ms/epoch - 6ms/step
Epoch 226/250
141/141 - 1s - loss: 0.0686 - categorical_accuracy: 0.9767 - val_loss: 0.1540 - val_categorical_accuracy: 0.9561 - 860ms/epoch - 6ms/step
Epoch 227/250
141/141 - 1s - loss: 0.0631 - categorical_accuracy: 0.9784 - val_loss: 0.1447 - val_categorical_accuracy: 0.9582 - 859ms/epoch - 6ms/step
Epoch 228/250
141/141 - 1s - loss: 0.0644 - categorical_accuracy: 0.9778 - val_loss: 0.1955 - val_categorical_accuracy: 0.9471 - 857ms/epoch - 6ms/step
Epoch 229/250
141/141 - 1s - loss: 0.1569 - categorical_accuracy: 0.9557 - val_loss: 0.1569 - val_categorical_accuracy: 0.9517 - 863ms/epoch - 6ms/step
Epoch 230/250
141/141 - 1s - loss: 0.0666 - categorical_accuracy: 0.9777 - val_loss: 0.1428 - val_categorical_accuracy: 0.9576 - 876ms/epoch - 6ms/step
Epoch 231/250
141/141 - 1s - loss: 0.0686 - categorical_accuracy: 0.9767 - val_loss: 0.1511 - val_categorical_accuracy: 0.9561 - 859ms/epoch - 6ms/step
Epoch 232/250
141/141 - 1s - loss: 0.0632 - categorical_accuracy: 0.9785 - val_loss: 0.1497 - val_categorical_accuracy: 0.9557 - 860ms/epoch - 6ms/step
Epoch 233/250
141/141 - 1s - loss: 0.0657 - categorical_accuracy: 0.9776 - val_loss: 0.1460 - val_categorical_accuracy: 0.9596 - 862ms/epoch - 6ms/step
Epoch 234/250
141/141 - 1s - loss: 0.0643 - categorical_accuracy: 0.9778 - val_loss: 0.1614 - val_categorical_accuracy: 0.9534 - 843ms/epoch - 6ms/step
Epoch 235/250
141/141 - 1s - loss: 0.0753 - categorical_accuracy: 0.9740 - val_loss: 0.1584 - val_categorical_accuracy: 0.9527 - 860ms/epoch - 6ms/step
Epoch 236/250
141/141 - 1s - loss: 0.0633 - categorical_accuracy: 0.9784 - val_loss: 0.1732 - val_categorical_accuracy: 0.9538 - 858ms/epoch - 6ms/step
Epoch 237/250
141/141 - 1s - loss: 0.0648 - categorical_accuracy: 0.9775 - val_loss: 0.1544 - val_categorical_accuracy: 0.9561 - 875ms/epoch - 6ms/step
Epoch 238/250
141/141 - 1s - loss: 0.0656 - categorical_accuracy: 0.9776 - val_loss: 0.1597 - val_categorical_accuracy: 0.9542 - 843ms/epoch - 6ms/step
Epoch 239/250
141/141 - 1s - loss: 0.0817 - categorical_accuracy: 0.9731 - val_loss: 0.7263 - val_categorical_accuracy: 0.8131 - 861ms/epoch - 6ms/step
Epoch 240/250
141/141 - 1s - loss: 0.0812 - categorical_accuracy: 0.9729 - val_loss: 0.1554 - val_categorical_accuracy: 0.9534 - 844ms/epoch - 6ms/step
Epoch 241/250
141/141 - 1s - loss: 0.0621 - categorical_accuracy: 0.9787 - val_loss: 0.1590 - val_categorical_accuracy: 0.9568 - 856ms/epoch - 6ms/step
Epoch 242/250
141/141 - 1s - loss: 0.0619 - categorical_accuracy: 0.9788 - val_loss: 0.1871 - val_categorical_accuracy: 0.9508 - 852ms/epoch - 6ms/step
Epoch 243/250
141/141 - 1s - loss: 0.0628 - categorical_accuracy: 0.9784 - val_loss: 0.1747 - val_categorical_accuracy: 0.9520 - 871ms/epoch - 6ms/step
Epoch 244/250
141/141 - 1s - loss: 0.0693 - categorical_accuracy: 0.9762 - val_loss: 0.1635 - val_categorical_accuracy: 0.9518 - 861ms/epoch - 6ms/step
Epoch 245/250
141/141 - 1s - loss: 0.0629 - categorical_accuracy: 0.9786 - val_loss: 0.1542 - val_categorical_accuracy: 0.9583 - 859ms/epoch - 6ms/step
Epoch 246/250
141/141 - 1s - loss: 0.0659 - categorical_accuracy: 0.9772 - val_loss: 0.1684 - val_categorical_accuracy: 0.9528 - 856ms/epoch - 6ms/step
Epoch 247/250
141/141 - 1s - loss: 0.0626 - categorical_accuracy: 0.9784 - val_loss: 0.1789 - val_categorical_accuracy: 0.9509 - 876ms/epoch - 6ms/step
Epoch 248/250
141/141 - 1s - loss: 0.0942 - categorical_accuracy: 0.9702 - val_loss: 0.1534 - val_categorical_accuracy: 0.9554 - 861ms/epoch - 6ms/step
Epoch 249/250
141/141 - 1s - loss: 0.0624 - categorical_accuracy: 0.9788 - val_loss: 0.1645 - val_categorical_accuracy: 0.9515 - 862ms/epoch - 6ms/step
Epoch 250/250
141/141 - 1s - loss: 0.0602 - categorical_accuracy: 0.9791 - val_loss: 0.1603 - val_categorical_accuracy: 0.9542 - 860ms/epoch - 6ms/step
processing fold # 2 
Epoch 1/250
141/141 - 2s - loss: 1.9346 - categorical_accuracy: 0.2727 - val_loss: 1.7254 - val_categorical_accuracy: 0.3449 - 2s/epoch - 12ms/step
Epoch 2/250
141/141 - 1s - loss: 1.5527 - categorical_accuracy: 0.4232 - val_loss: 1.4494 - val_categorical_accuracy: 0.4816 - 904ms/epoch - 6ms/step
Epoch 3/250
141/141 - 1s - loss: 1.3002 - categorical_accuracy: 0.5138 - val_loss: 1.0886 - val_categorical_accuracy: 0.5874 - 862ms/epoch - 6ms/step
Epoch 4/250
141/141 - 1s - loss: 1.1165 - categorical_accuracy: 0.5789 - val_loss: 1.0370 - val_categorical_accuracy: 0.5941 - 879ms/epoch - 6ms/step
Epoch 5/250
141/141 - 1s - loss: 0.9919 - categorical_accuracy: 0.6269 - val_loss: 1.0312 - val_categorical_accuracy: 0.6190 - 858ms/epoch - 6ms/step
Epoch 6/250
141/141 - 1s - loss: 0.8758 - categorical_accuracy: 0.6689 - val_loss: 0.9553 - val_categorical_accuracy: 0.6410 - 876ms/epoch - 6ms/step
Epoch 7/250
141/141 - 1s - loss: 0.7908 - categorical_accuracy: 0.7019 - val_loss: 0.6767 - val_categorical_accuracy: 0.7434 - 846ms/epoch - 6ms/step
Epoch 8/250
141/141 - 1s - loss: 0.7570 - categorical_accuracy: 0.7194 - val_loss: 0.6366 - val_categorical_accuracy: 0.7547 - 874ms/epoch - 6ms/step
Epoch 9/250
141/141 - 1s - loss: 0.7488 - categorical_accuracy: 0.7266 - val_loss: 0.6576 - val_categorical_accuracy: 0.7421 - 876ms/epoch - 6ms/step
Epoch 10/250
141/141 - 1s - loss: 0.6330 - categorical_accuracy: 0.7623 - val_loss: 0.5784 - val_categorical_accuracy: 0.7788 - 878ms/epoch - 6ms/step
Epoch 11/250
141/141 - 1s - loss: 0.6094 - categorical_accuracy: 0.7742 - val_loss: 0.5943 - val_categorical_accuracy: 0.7817 - 859ms/epoch - 6ms/step
Epoch 12/250
141/141 - 1s - loss: 0.6310 - categorical_accuracy: 0.7708 - val_loss: 0.7108 - val_categorical_accuracy: 0.7336 - 859ms/epoch - 6ms/step
Epoch 13/250
141/141 - 1s - loss: 0.6202 - categorical_accuracy: 0.7785 - val_loss: 0.4770 - val_categorical_accuracy: 0.8256 - 860ms/epoch - 6ms/step
Epoch 14/250
141/141 - 1s - loss: 0.5655 - categorical_accuracy: 0.7962 - val_loss: 2.8087 - val_categorical_accuracy: 0.2790 - 878ms/epoch - 6ms/step
Epoch 15/250
141/141 - 1s - loss: 0.6189 - categorical_accuracy: 0.7781 - val_loss: 0.7205 - val_categorical_accuracy: 0.7405 - 874ms/epoch - 6ms/step
Epoch 16/250
141/141 - 1s - loss: 0.4786 - categorical_accuracy: 0.8248 - val_loss: 0.4246 - val_categorical_accuracy: 0.8469 - 881ms/epoch - 6ms/step
Epoch 17/250
141/141 - 1s - loss: 0.4745 - categorical_accuracy: 0.8272 - val_loss: 0.4003 - val_categorical_accuracy: 0.8540 - 854ms/epoch - 6ms/step
Epoch 18/250
141/141 - 1s - loss: 0.4277 - categorical_accuracy: 0.8425 - val_loss: 0.4001 - val_categorical_accuracy: 0.8601 - 875ms/epoch - 6ms/step
Epoch 19/250
141/141 - 1s - loss: 0.4708 - categorical_accuracy: 0.8341 - val_loss: 0.4353 - val_categorical_accuracy: 0.8420 - 904ms/epoch - 6ms/step
Epoch 20/250
141/141 - 1s - loss: 0.3976 - categorical_accuracy: 0.8538 - val_loss: 0.4113 - val_categorical_accuracy: 0.8526 - 1s/epoch - 9ms/step
Epoch 21/250
141/141 - 1s - loss: 0.4148 - categorical_accuracy: 0.8531 - val_loss: 0.3554 - val_categorical_accuracy: 0.8711 - 989ms/epoch - 7ms/step
Epoch 22/250
141/141 - 1s - loss: 0.3781 - categorical_accuracy: 0.8630 - val_loss: 0.3823 - val_categorical_accuracy: 0.8637 - 969ms/epoch - 7ms/step
Epoch 23/250
141/141 - 1s - loss: 0.3561 - categorical_accuracy: 0.8708 - val_loss: 0.3607 - val_categorical_accuracy: 0.8701 - 937ms/epoch - 7ms/step
Epoch 24/250
141/141 - 1s - loss: 0.3444 - categorical_accuracy: 0.8746 - val_loss: 0.4004 - val_categorical_accuracy: 0.8552 - 950ms/epoch - 7ms/step
Epoch 25/250
141/141 - 1s - loss: 0.3529 - categorical_accuracy: 0.8741 - val_loss: 0.3771 - val_categorical_accuracy: 0.8614 - 965ms/epoch - 7ms/step
Epoch 26/250
141/141 - 1s - loss: 0.3234 - categorical_accuracy: 0.8831 - val_loss: 0.4056 - val_categorical_accuracy: 0.8490 - 938ms/epoch - 7ms/step
Epoch 27/250
141/141 - 1s - loss: 0.4091 - categorical_accuracy: 0.8628 - val_loss: 0.3195 - val_categorical_accuracy: 0.8863 - 943ms/epoch - 7ms/step
Epoch 28/250
141/141 - 1s - loss: 0.3161 - categorical_accuracy: 0.8867 - val_loss: 0.3014 - val_categorical_accuracy: 0.8937 - 958ms/epoch - 7ms/step
Epoch 29/250
141/141 - 1s - loss: 0.2952 - categorical_accuracy: 0.8931 - val_loss: 0.2954 - val_categorical_accuracy: 0.8958 - 970ms/epoch - 7ms/step
Epoch 30/250
141/141 - 1s - loss: 0.2952 - categorical_accuracy: 0.8940 - val_loss: 0.3336 - val_categorical_accuracy: 0.8800 - 937ms/epoch - 7ms/step
Epoch 31/250
141/141 - 1s - loss: 0.3514 - categorical_accuracy: 0.8810 - val_loss: 0.3203 - val_categorical_accuracy: 0.8853 - 970ms/epoch - 7ms/step
Epoch 32/250
141/141 - 1s - loss: 0.2843 - categorical_accuracy: 0.8984 - val_loss: 0.3160 - val_categorical_accuracy: 0.8875 - 986ms/epoch - 7ms/step
Epoch 33/250
141/141 - 1s - loss: 0.2720 - categorical_accuracy: 0.9024 - val_loss: 0.2714 - val_categorical_accuracy: 0.9040 - 954ms/epoch - 7ms/step
Epoch 34/250
141/141 - 1s - loss: 0.2764 - categorical_accuracy: 0.9021 - val_loss: 0.3045 - val_categorical_accuracy: 0.8923 - 939ms/epoch - 7ms/step
Epoch 35/250
141/141 - 1s - loss: 0.2582 - categorical_accuracy: 0.9077 - val_loss: 0.3022 - val_categorical_accuracy: 0.8913 - 985ms/epoch - 7ms/step
Epoch 36/250
141/141 - 1s - loss: 0.2563 - categorical_accuracy: 0.9085 - val_loss: 0.2768 - val_categorical_accuracy: 0.9026 - 987ms/epoch - 7ms/step
Epoch 37/250
141/141 - 1s - loss: 0.2607 - categorical_accuracy: 0.9091 - val_loss: 0.2971 - val_categorical_accuracy: 0.8930 - 956ms/epoch - 7ms/step
Epoch 38/250
141/141 - 1s - loss: 0.4097 - categorical_accuracy: 0.8685 - val_loss: 0.4482 - val_categorical_accuracy: 0.8431 - 957ms/epoch - 7ms/step
Epoch 39/250
141/141 - 1s - loss: 0.2689 - categorical_accuracy: 0.9061 - val_loss: 0.2650 - val_categorical_accuracy: 0.9051 - 953ms/epoch - 7ms/step
Epoch 40/250
141/141 - 1s - loss: 0.3822 - categorical_accuracy: 0.8780 - val_loss: 0.2929 - val_categorical_accuracy: 0.8943 - 969ms/epoch - 7ms/step
Epoch 41/250
141/141 - 1s - loss: 0.2494 - categorical_accuracy: 0.9124 - val_loss: 0.2499 - val_categorical_accuracy: 0.9111 - 942ms/epoch - 7ms/step
Epoch 42/250
141/141 - 1s - loss: 0.2260 - categorical_accuracy: 0.9199 - val_loss: 0.2507 - val_categorical_accuracy: 0.9097 - 969ms/epoch - 7ms/step
Epoch 43/250
141/141 - 1s - loss: 0.2358 - categorical_accuracy: 0.9170 - val_loss: 0.2420 - val_categorical_accuracy: 0.9150 - 941ms/epoch - 7ms/step
Epoch 44/250
141/141 - 1s - loss: 0.2389 - categorical_accuracy: 0.9186 - val_loss: 0.2371 - val_categorical_accuracy: 0.9156 - 938ms/epoch - 7ms/step
Epoch 45/250
141/141 - 1s - loss: 0.2203 - categorical_accuracy: 0.9229 - val_loss: 0.2254 - val_categorical_accuracy: 0.9219 - 952ms/epoch - 7ms/step
Epoch 46/250
141/141 - 1s - loss: 0.2201 - categorical_accuracy: 0.9226 - val_loss: 0.2211 - val_categorical_accuracy: 0.9218 - 953ms/epoch - 7ms/step
Epoch 47/250
141/141 - 1s - loss: 0.2131 - categorical_accuracy: 0.9247 - val_loss: 0.2547 - val_categorical_accuracy: 0.9101 - 941ms/epoch - 7ms/step
Epoch 48/250
141/141 - 1s - loss: 0.2682 - categorical_accuracy: 0.9122 - val_loss: 0.2308 - val_categorical_accuracy: 0.9197 - 959ms/epoch - 7ms/step
Epoch 49/250
141/141 - 1s - loss: 0.1976 - categorical_accuracy: 0.9303 - val_loss: 0.2648 - val_categorical_accuracy: 0.9090 - 921ms/epoch - 7ms/step
Epoch 50/250
141/141 - 1s - loss: 0.1978 - categorical_accuracy: 0.9306 - val_loss: 0.2228 - val_categorical_accuracy: 0.9231 - 895ms/epoch - 6ms/step
Epoch 51/250
141/141 - 1s - loss: 0.2007 - categorical_accuracy: 0.9289 - val_loss: 0.2096 - val_categorical_accuracy: 0.9276 - 904ms/epoch - 6ms/step
Epoch 52/250
141/141 - 1s - loss: 0.1960 - categorical_accuracy: 0.9305 - val_loss: 0.2171 - val_categorical_accuracy: 0.9237 - 888ms/epoch - 6ms/step
Epoch 53/250
141/141 - 1s - loss: 0.1870 - categorical_accuracy: 0.9346 - val_loss: 0.2455 - val_categorical_accuracy: 0.9177 - 886ms/epoch - 6ms/step
Epoch 54/250
141/141 - 1s - loss: 0.4475 - categorical_accuracy: 0.8599 - val_loss: 0.3526 - val_categorical_accuracy: 0.8735 - 909ms/epoch - 6ms/step
Epoch 55/250
141/141 - 1s - loss: 0.2245 - categorical_accuracy: 0.9212 - val_loss: 0.2284 - val_categorical_accuracy: 0.9221 - 923ms/epoch - 7ms/step
Epoch 56/250
141/141 - 1s - loss: 0.1958 - categorical_accuracy: 0.9310 - val_loss: 0.2140 - val_categorical_accuracy: 0.9265 - 875ms/epoch - 6ms/step
Epoch 57/250
141/141 - 1s - loss: 0.1904 - categorical_accuracy: 0.9331 - val_loss: 0.2312 - val_categorical_accuracy: 0.9212 - 905ms/epoch - 6ms/step
Epoch 58/250
141/141 - 1s - loss: 0.1807 - categorical_accuracy: 0.9370 - val_loss: 0.2110 - val_categorical_accuracy: 0.9263 - 910ms/epoch - 6ms/step
Epoch 59/250
141/141 - 1s - loss: 0.1779 - categorical_accuracy: 0.9374 - val_loss: 0.1967 - val_categorical_accuracy: 0.9321 - 894ms/epoch - 6ms/step
Epoch 60/250
141/141 - 1s - loss: 0.2447 - categorical_accuracy: 0.9227 - val_loss: 0.2298 - val_categorical_accuracy: 0.9170 - 904ms/epoch - 6ms/step
Epoch 61/250
141/141 - 1s - loss: 0.1794 - categorical_accuracy: 0.9379 - val_loss: 0.3340 - val_categorical_accuracy: 0.8803 - 908ms/epoch - 6ms/step
Epoch 62/250
141/141 - 1s - loss: 0.1764 - categorical_accuracy: 0.9392 - val_loss: 0.2310 - val_categorical_accuracy: 0.9198 - 894ms/epoch - 6ms/step
Epoch 63/250
141/141 - 1s - loss: 0.1693 - categorical_accuracy: 0.9410 - val_loss: 0.2789 - val_categorical_accuracy: 0.9048 - 893ms/epoch - 6ms/step
Epoch 64/250
141/141 - 1s - loss: 0.2619 - categorical_accuracy: 0.9177 - val_loss: 0.1863 - val_categorical_accuracy: 0.9365 - 875ms/epoch - 6ms/step
Epoch 65/250
141/141 - 1s - loss: 0.1615 - categorical_accuracy: 0.9439 - val_loss: 0.1941 - val_categorical_accuracy: 0.9336 - 920ms/epoch - 7ms/step
Epoch 66/250
141/141 - 1s - loss: 0.1657 - categorical_accuracy: 0.9424 - val_loss: 0.2156 - val_categorical_accuracy: 0.9263 - 926ms/epoch - 7ms/step
Epoch 67/250
141/141 - 1s - loss: 0.2041 - categorical_accuracy: 0.9328 - val_loss: 0.1819 - val_categorical_accuracy: 0.9395 - 894ms/epoch - 6ms/step
Epoch 68/250
141/141 - 1s - loss: 0.1504 - categorical_accuracy: 0.9484 - val_loss: 0.2068 - val_categorical_accuracy: 0.9280 - 906ms/epoch - 6ms/step
Epoch 69/250
141/141 - 1s - loss: 0.1604 - categorical_accuracy: 0.9443 - val_loss: 0.2028 - val_categorical_accuracy: 0.9322 - 940ms/epoch - 7ms/step
Epoch 70/250
141/141 - 1s - loss: 0.1555 - categorical_accuracy: 0.9461 - val_loss: 0.1998 - val_categorical_accuracy: 0.9331 - 925ms/epoch - 7ms/step
Epoch 71/250
141/141 - 1s - loss: 0.1645 - categorical_accuracy: 0.9433 - val_loss: 0.2264 - val_categorical_accuracy: 0.9242 - 909ms/epoch - 6ms/step
Epoch 72/250
141/141 - 1s - loss: 0.1542 - categorical_accuracy: 0.9468 - val_loss: 0.3611 - val_categorical_accuracy: 0.8802 - 892ms/epoch - 6ms/step
Epoch 73/250
141/141 - 1s - loss: 0.2173 - categorical_accuracy: 0.9327 - val_loss: 0.1983 - val_categorical_accuracy: 0.9295 - 905ms/epoch - 6ms/step
Epoch 74/250
141/141 - 1s - loss: 0.1443 - categorical_accuracy: 0.9500 - val_loss: 0.2026 - val_categorical_accuracy: 0.9317 - 907ms/epoch - 6ms/step
Epoch 75/250
141/141 - 1s - loss: 0.1598 - categorical_accuracy: 0.9446 - val_loss: 0.2466 - val_categorical_accuracy: 0.9165 - 875ms/epoch - 6ms/step
Epoch 76/250
141/141 - 1s - loss: 0.1451 - categorical_accuracy: 0.9504 - val_loss: 0.1698 - val_categorical_accuracy: 0.9442 - 893ms/epoch - 6ms/step
Epoch 77/250
141/141 - 1s - loss: 0.1449 - categorical_accuracy: 0.9501 - val_loss: 0.1832 - val_categorical_accuracy: 0.9389 - 890ms/epoch - 6ms/step
Epoch 78/250
141/141 - 1s - loss: 0.1383 - categorical_accuracy: 0.9523 - val_loss: 0.1950 - val_categorical_accuracy: 0.9348 - 906ms/epoch - 6ms/step
Epoch 79/250
141/141 - 1s - loss: 0.5219 - categorical_accuracy: 0.8441 - val_loss: 0.2216 - val_categorical_accuracy: 0.9231 - 940ms/epoch - 7ms/step
Epoch 80/250
141/141 - 1s - loss: 0.1667 - categorical_accuracy: 0.9419 - val_loss: 0.1914 - val_categorical_accuracy: 0.9352 - 892ms/epoch - 6ms/step
Epoch 81/250
141/141 - 1s - loss: 0.1448 - categorical_accuracy: 0.9497 - val_loss: 0.1884 - val_categorical_accuracy: 0.9341 - 911ms/epoch - 6ms/step
Epoch 82/250
141/141 - 1s - loss: 0.1401 - categorical_accuracy: 0.9512 - val_loss: 0.2440 - val_categorical_accuracy: 0.9185 - 908ms/epoch - 6ms/step
Epoch 83/250
141/141 - 1s - loss: 0.1912 - categorical_accuracy: 0.9384 - val_loss: 0.1844 - val_categorical_accuracy: 0.9378 - 906ms/epoch - 6ms/step
Epoch 84/250
141/141 - 1s - loss: 0.1391 - categorical_accuracy: 0.9519 - val_loss: 0.1825 - val_categorical_accuracy: 0.9378 - 908ms/epoch - 6ms/step
Epoch 85/250
141/141 - 1s - loss: 0.1326 - categorical_accuracy: 0.9543 - val_loss: 0.1859 - val_categorical_accuracy: 0.9369 - 892ms/epoch - 6ms/step
Epoch 86/250
141/141 - 1s - loss: 0.1456 - categorical_accuracy: 0.9508 - val_loss: 0.1651 - val_categorical_accuracy: 0.9435 - 887ms/epoch - 6ms/step
Epoch 87/250
141/141 - 1s - loss: 0.1351 - categorical_accuracy: 0.9533 - val_loss: 0.2458 - val_categorical_accuracy: 0.9142 - 887ms/epoch - 6ms/step
Epoch 88/250
141/141 - 1s - loss: 0.1337 - categorical_accuracy: 0.9538 - val_loss: 0.1928 - val_categorical_accuracy: 0.9342 - 889ms/epoch - 6ms/step
Epoch 89/250
141/141 - 1s - loss: 0.1359 - categorical_accuracy: 0.9533 - val_loss: 0.1887 - val_categorical_accuracy: 0.9368 - 894ms/epoch - 6ms/step
Epoch 90/250
141/141 - 1s - loss: 0.1280 - categorical_accuracy: 0.9560 - val_loss: 0.2749 - val_categorical_accuracy: 0.9031 - 908ms/epoch - 6ms/step
Epoch 91/250
141/141 - 1s - loss: 0.1301 - categorical_accuracy: 0.9555 - val_loss: 0.4096 - val_categorical_accuracy: 0.8833 - 876ms/epoch - 6ms/step
Epoch 92/250
141/141 - 1s - loss: 0.1310 - categorical_accuracy: 0.9551 - val_loss: 0.1981 - val_categorical_accuracy: 0.9356 - 876ms/epoch - 6ms/step
Epoch 93/250
141/141 - 1s - loss: 0.1257 - categorical_accuracy: 0.9567 - val_loss: 0.1776 - val_categorical_accuracy: 0.9392 - 892ms/epoch - 6ms/step
Epoch 94/250
141/141 - 1s - loss: 0.1338 - categorical_accuracy: 0.9548 - val_loss: 0.1867 - val_categorical_accuracy: 0.9374 - 895ms/epoch - 6ms/step
Epoch 95/250
141/141 - 1s - loss: 0.1334 - categorical_accuracy: 0.9540 - val_loss: 0.1790 - val_categorical_accuracy: 0.9379 - 891ms/epoch - 6ms/step
Epoch 96/250
141/141 - 1s - loss: 0.1645 - categorical_accuracy: 0.9485 - val_loss: 0.1607 - val_categorical_accuracy: 0.9467 - 922ms/epoch - 7ms/step
Epoch 97/250
141/141 - 1s - loss: 0.1176 - categorical_accuracy: 0.9599 - val_loss: 0.2142 - val_categorical_accuracy: 0.9293 - 921ms/epoch - 7ms/step
Epoch 98/250
141/141 - 1s - loss: 0.1559 - categorical_accuracy: 0.9504 - val_loss: 0.1671 - val_categorical_accuracy: 0.9457 - 909ms/epoch - 6ms/step
Epoch 99/250
141/141 - 1s - loss: 0.1332 - categorical_accuracy: 0.9557 - val_loss: 0.1618 - val_categorical_accuracy: 0.9446 - 910ms/epoch - 6ms/step
Epoch 100/250
141/141 - 1s - loss: 0.1101 - categorical_accuracy: 0.9625 - val_loss: 0.3184 - val_categorical_accuracy: 0.8843 - 908ms/epoch - 6ms/step
Epoch 101/250
141/141 - 1s - loss: 0.1344 - categorical_accuracy: 0.9554 - val_loss: 0.1606 - val_categorical_accuracy: 0.9451 - 923ms/epoch - 7ms/step
Epoch 102/250
141/141 - 1s - loss: 0.1094 - categorical_accuracy: 0.9623 - val_loss: 0.1612 - val_categorical_accuracy: 0.9459 - 926ms/epoch - 7ms/step
Epoch 103/250
141/141 - 1s - loss: 0.1251 - categorical_accuracy: 0.9577 - val_loss: 0.1689 - val_categorical_accuracy: 0.9448 - 911ms/epoch - 6ms/step
Epoch 104/250
141/141 - 1s - loss: 0.1175 - categorical_accuracy: 0.9594 - val_loss: 0.1763 - val_categorical_accuracy: 0.9455 - 921ms/epoch - 7ms/step
Epoch 105/250
141/141 - 1s - loss: 0.1091 - categorical_accuracy: 0.9622 - val_loss: 0.1820 - val_categorical_accuracy: 0.9385 - 894ms/epoch - 6ms/step
Epoch 106/250
141/141 - 1s - loss: 0.1127 - categorical_accuracy: 0.9608 - val_loss: 0.1496 - val_categorical_accuracy: 0.9510 - 903ms/epoch - 6ms/step
Epoch 107/250
141/141 - 1s - loss: 0.1258 - categorical_accuracy: 0.9579 - val_loss: 0.1840 - val_categorical_accuracy: 0.9356 - 904ms/epoch - 6ms/step
Epoch 108/250
141/141 - 1s - loss: 0.1089 - categorical_accuracy: 0.9627 - val_loss: 0.1528 - val_categorical_accuracy: 0.9501 - 925ms/epoch - 7ms/step
Epoch 109/250
141/141 - 1s - loss: 0.1199 - categorical_accuracy: 0.9598 - val_loss: 0.1554 - val_categorical_accuracy: 0.9483 - 923ms/epoch - 7ms/step
Epoch 110/250
141/141 - 1s - loss: 0.1419 - categorical_accuracy: 0.9545 - val_loss: 0.1602 - val_categorical_accuracy: 0.9492 - 921ms/epoch - 7ms/step
Epoch 111/250
141/141 - 1s - loss: 0.1120 - categorical_accuracy: 0.9620 - val_loss: 0.1904 - val_categorical_accuracy: 0.9344 - 956ms/epoch - 7ms/step
Epoch 112/250
141/141 - 1s - loss: 0.1098 - categorical_accuracy: 0.9622 - val_loss: 0.1570 - val_categorical_accuracy: 0.9479 - 910ms/epoch - 6ms/step
Epoch 113/250
141/141 - 1s - loss: 0.1193 - categorical_accuracy: 0.9603 - val_loss: 0.1593 - val_categorical_accuracy: 0.9475 - 907ms/epoch - 6ms/step
Epoch 114/250
141/141 - 1s - loss: 0.1168 - categorical_accuracy: 0.9609 - val_loss: 0.2067 - val_categorical_accuracy: 0.9352 - 923ms/epoch - 7ms/step
Epoch 115/250
141/141 - 1s - loss: 0.1097 - categorical_accuracy: 0.9619 - val_loss: 0.1642 - val_categorical_accuracy: 0.9450 - 926ms/epoch - 7ms/step
Epoch 116/250
141/141 - 1s - loss: 0.1098 - categorical_accuracy: 0.9626 - val_loss: 0.1742 - val_categorical_accuracy: 0.9401 - 925ms/epoch - 7ms/step
Epoch 117/250
141/141 - 1s - loss: 0.1050 - categorical_accuracy: 0.9639 - val_loss: 0.1680 - val_categorical_accuracy: 0.9476 - 907ms/epoch - 6ms/step
Epoch 118/250
141/141 - 1s - loss: 0.1115 - categorical_accuracy: 0.9624 - val_loss: 0.1536 - val_categorical_accuracy: 0.9496 - 896ms/epoch - 6ms/step
Epoch 119/250
141/141 - 1s - loss: 0.1031 - categorical_accuracy: 0.9644 - val_loss: 0.1703 - val_categorical_accuracy: 0.9471 - 907ms/epoch - 6ms/step
Epoch 120/250
141/141 - 1s - loss: 0.1816 - categorical_accuracy: 0.9465 - val_loss: 0.1656 - val_categorical_accuracy: 0.9433 - 919ms/epoch - 7ms/step
Epoch 121/250
141/141 - 1s - loss: 0.0976 - categorical_accuracy: 0.9667 - val_loss: 0.1661 - val_categorical_accuracy: 0.9462 - 924ms/epoch - 7ms/step
Epoch 122/250
141/141 - 1s - loss: 0.0995 - categorical_accuracy: 0.9660 - val_loss: 0.1642 - val_categorical_accuracy: 0.9488 - 923ms/epoch - 7ms/step
Epoch 123/250
141/141 - 1s - loss: 0.1123 - categorical_accuracy: 0.9631 - val_loss: 0.1814 - val_categorical_accuracy: 0.9438 - 925ms/epoch - 7ms/step
Epoch 124/250
141/141 - 1s - loss: 0.1044 - categorical_accuracy: 0.9644 - val_loss: 0.1565 - val_categorical_accuracy: 0.9509 - 925ms/epoch - 7ms/step
Epoch 125/250
141/141 - 1s - loss: 0.0965 - categorical_accuracy: 0.9669 - val_loss: 0.1757 - val_categorical_accuracy: 0.9464 - 911ms/epoch - 6ms/step
Epoch 126/250
141/141 - 1s - loss: 0.1471 - categorical_accuracy: 0.9548 - val_loss: 0.1556 - val_categorical_accuracy: 0.9505 - 925ms/epoch - 7ms/step
Epoch 127/250
141/141 - 1s - loss: 0.0938 - categorical_accuracy: 0.9680 - val_loss: 0.2060 - val_categorical_accuracy: 0.9376 - 938ms/epoch - 7ms/step
Epoch 128/250
141/141 - 1s - loss: 0.0954 - categorical_accuracy: 0.9670 - val_loss: 0.1554 - val_categorical_accuracy: 0.9486 - 934ms/epoch - 7ms/step
Epoch 129/250
141/141 - 1s - loss: 0.1136 - categorical_accuracy: 0.9628 - val_loss: 0.1529 - val_categorical_accuracy: 0.9520 - 908ms/epoch - 6ms/step
Epoch 130/250
141/141 - 1s - loss: 0.1023 - categorical_accuracy: 0.9648 - val_loss: 0.1491 - val_categorical_accuracy: 0.9528 - 925ms/epoch - 7ms/step
Epoch 131/250
141/141 - 1s - loss: 0.0903 - categorical_accuracy: 0.9690 - val_loss: 0.1713 - val_categorical_accuracy: 0.9431 - 937ms/epoch - 7ms/step
Epoch 132/250
141/141 - 1s - loss: 0.1078 - categorical_accuracy: 0.9643 - val_loss: 0.1776 - val_categorical_accuracy: 0.9460 - 911ms/epoch - 6ms/step
Epoch 133/250
141/141 - 1s - loss: 0.1209 - categorical_accuracy: 0.9609 - val_loss: 0.1528 - val_categorical_accuracy: 0.9522 - 893ms/epoch - 6ms/step
Epoch 134/250
141/141 - 1s - loss: 0.0931 - categorical_accuracy: 0.9686 - val_loss: 0.2224 - val_categorical_accuracy: 0.9322 - 921ms/epoch - 7ms/step
Epoch 135/250
141/141 - 1s - loss: 0.0920 - categorical_accuracy: 0.9683 - val_loss: 0.2502 - val_categorical_accuracy: 0.9215 - 926ms/epoch - 7ms/step
Epoch 136/250
141/141 - 1s - loss: 0.1121 - categorical_accuracy: 0.9624 - val_loss: 0.1674 - val_categorical_accuracy: 0.9491 - 924ms/epoch - 7ms/step
Epoch 137/250
141/141 - 1s - loss: 0.0952 - categorical_accuracy: 0.9674 - val_loss: 0.1473 - val_categorical_accuracy: 0.9520 - 909ms/epoch - 6ms/step
Epoch 138/250
141/141 - 1s - loss: 0.0858 - categorical_accuracy: 0.9705 - val_loss: 0.1884 - val_categorical_accuracy: 0.9433 - 923ms/epoch - 7ms/step
Epoch 139/250
141/141 - 1s - loss: 0.0951 - categorical_accuracy: 0.9673 - val_loss: 0.1617 - val_categorical_accuracy: 0.9472 - 905ms/epoch - 6ms/step
Epoch 140/250
141/141 - 1s - loss: 0.0934 - categorical_accuracy: 0.9681 - val_loss: 1.2991 - val_categorical_accuracy: 0.7611 - 935ms/epoch - 7ms/step
Epoch 141/250
141/141 - 1s - loss: 0.1454 - categorical_accuracy: 0.9564 - val_loss: 0.1637 - val_categorical_accuracy: 0.9489 - 908ms/epoch - 6ms/step
Epoch 142/250
141/141 - 1s - loss: 0.0863 - categorical_accuracy: 0.9704 - val_loss: 0.1504 - val_categorical_accuracy: 0.9535 - 923ms/epoch - 7ms/step
Epoch 143/250
141/141 - 1s - loss: 0.1442 - categorical_accuracy: 0.9567 - val_loss: 0.1753 - val_categorical_accuracy: 0.9406 - 907ms/epoch - 6ms/step
Epoch 144/250
141/141 - 1s - loss: 0.0842 - categorical_accuracy: 0.9717 - val_loss: 0.1544 - val_categorical_accuracy: 0.9489 - 907ms/epoch - 6ms/step
Epoch 145/250
141/141 - 1s - loss: 0.0845 - categorical_accuracy: 0.9709 - val_loss: 0.1577 - val_categorical_accuracy: 0.9483 - 927ms/epoch - 7ms/step
Epoch 146/250
141/141 - 1s - loss: 0.1076 - categorical_accuracy: 0.9654 - val_loss: 0.1466 - val_categorical_accuracy: 0.9559 - 926ms/epoch - 7ms/step
Epoch 147/250
141/141 - 1s - loss: 0.0995 - categorical_accuracy: 0.9673 - val_loss: 1.1690 - val_categorical_accuracy: 0.7735 - 922ms/epoch - 7ms/step
Epoch 148/250
141/141 - 1s - loss: 0.0988 - categorical_accuracy: 0.9675 - val_loss: 0.1724 - val_categorical_accuracy: 0.9451 - 907ms/epoch - 6ms/step
Epoch 149/250
141/141 - 1s - loss: 0.0839 - categorical_accuracy: 0.9709 - val_loss: 0.1550 - val_categorical_accuracy: 0.9530 - 925ms/epoch - 7ms/step
Epoch 150/250
141/141 - 1s - loss: 0.1072 - categorical_accuracy: 0.9655 - val_loss: 0.1483 - val_categorical_accuracy: 0.9531 - 908ms/epoch - 6ms/step
Epoch 151/250
141/141 - 1s - loss: 0.0888 - categorical_accuracy: 0.9697 - val_loss: 0.1584 - val_categorical_accuracy: 0.9486 - 923ms/epoch - 7ms/step
Epoch 152/250
141/141 - 1s - loss: 0.0810 - categorical_accuracy: 0.9722 - val_loss: 0.1523 - val_categorical_accuracy: 0.9527 - 906ms/epoch - 6ms/step
Epoch 153/250
141/141 - 1s - loss: 0.0880 - categorical_accuracy: 0.9698 - val_loss: 0.1853 - val_categorical_accuracy: 0.9384 - 1s/epoch - 8ms/step
Epoch 154/250
141/141 - 1s - loss: 0.1006 - categorical_accuracy: 0.9665 - val_loss: 0.2325 - val_categorical_accuracy: 0.9261 - 925ms/epoch - 7ms/step
Epoch 155/250
141/141 - 1s - loss: 0.0993 - categorical_accuracy: 0.9674 - val_loss: 0.1620 - val_categorical_accuracy: 0.9510 - 923ms/epoch - 7ms/step
Epoch 156/250
141/141 - 1s - loss: 0.0833 - categorical_accuracy: 0.9714 - val_loss: 0.1469 - val_categorical_accuracy: 0.9542 - 908ms/epoch - 6ms/step
Epoch 157/250
141/141 - 1s - loss: 0.0962 - categorical_accuracy: 0.9682 - val_loss: 0.1492 - val_categorical_accuracy: 0.9546 - 877ms/epoch - 6ms/step
Epoch 158/250
141/141 - 1s - loss: 0.0866 - categorical_accuracy: 0.9704 - val_loss: 0.1743 - val_categorical_accuracy: 0.9490 - 878ms/epoch - 6ms/step
Epoch 159/250
141/141 - 1s - loss: 0.0825 - categorical_accuracy: 0.9714 - val_loss: 0.1784 - val_categorical_accuracy: 0.9443 - 877ms/epoch - 6ms/step
Epoch 160/250
141/141 - 1s - loss: 0.1534 - categorical_accuracy: 0.9541 - val_loss: 0.1581 - val_categorical_accuracy: 0.9513 - 862ms/epoch - 6ms/step
Epoch 161/250
141/141 - 1s - loss: 0.0811 - categorical_accuracy: 0.9725 - val_loss: 0.1565 - val_categorical_accuracy: 0.9518 - 862ms/epoch - 6ms/step
Epoch 162/250
141/141 - 1s - loss: 0.0804 - categorical_accuracy: 0.9723 - val_loss: 0.1481 - val_categorical_accuracy: 0.9537 - 879ms/epoch - 6ms/step
Epoch 163/250
141/141 - 1s - loss: 0.0837 - categorical_accuracy: 0.9713 - val_loss: 0.1449 - val_categorical_accuracy: 0.9546 - 858ms/epoch - 6ms/step
Epoch 164/250
141/141 - 1s - loss: 0.0921 - categorical_accuracy: 0.9689 - val_loss: 0.1413 - val_categorical_accuracy: 0.9566 - 861ms/epoch - 6ms/step
Epoch 165/250
141/141 - 1s - loss: 0.0769 - categorical_accuracy: 0.9737 - val_loss: 0.1513 - val_categorical_accuracy: 0.9525 - 862ms/epoch - 6ms/step
Epoch 166/250
141/141 - 1s - loss: 0.0769 - categorical_accuracy: 0.9737 - val_loss: 0.1515 - val_categorical_accuracy: 0.9552 - 876ms/epoch - 6ms/step
Epoch 167/250
141/141 - 1s - loss: 0.0758 - categorical_accuracy: 0.9738 - val_loss: 0.1528 - val_categorical_accuracy: 0.9539 - 895ms/epoch - 6ms/step
Epoch 168/250
141/141 - 1s - loss: 0.1339 - categorical_accuracy: 0.9596 - val_loss: 0.1698 - val_categorical_accuracy: 0.9438 - 862ms/epoch - 6ms/step
Epoch 169/250
141/141 - 1s - loss: 0.0749 - categorical_accuracy: 0.9746 - val_loss: 0.1669 - val_categorical_accuracy: 0.9471 - 876ms/epoch - 6ms/step
Epoch 170/250
141/141 - 1s - loss: 0.1190 - categorical_accuracy: 0.9626 - val_loss: 0.1644 - val_categorical_accuracy: 0.9461 - 875ms/epoch - 6ms/step
Epoch 171/250
141/141 - 1s - loss: 0.0733 - categorical_accuracy: 0.9754 - val_loss: 0.1476 - val_categorical_accuracy: 0.9572 - 862ms/epoch - 6ms/step
Epoch 172/250
141/141 - 1s - loss: 0.1304 - categorical_accuracy: 0.9596 - val_loss: 0.1604 - val_categorical_accuracy: 0.9507 - 844ms/epoch - 6ms/step
Epoch 173/250
141/141 - 1s - loss: 0.0739 - categorical_accuracy: 0.9752 - val_loss: 0.1461 - val_categorical_accuracy: 0.9567 - 861ms/epoch - 6ms/step
Epoch 174/250
141/141 - 1s - loss: 0.1035 - categorical_accuracy: 0.9670 - val_loss: 0.1512 - val_categorical_accuracy: 0.9534 - 873ms/epoch - 6ms/step
Epoch 175/250
141/141 - 1s - loss: 0.0769 - categorical_accuracy: 0.9738 - val_loss: 0.1675 - val_categorical_accuracy: 0.9489 - 875ms/epoch - 6ms/step
Epoch 176/250
141/141 - 1s - loss: 0.0762 - categorical_accuracy: 0.9740 - val_loss: 0.1583 - val_categorical_accuracy: 0.9539 - 878ms/epoch - 6ms/step
Epoch 177/250
141/141 - 1s - loss: 0.0737 - categorical_accuracy: 0.9748 - val_loss: 0.1452 - val_categorical_accuracy: 0.9549 - 878ms/epoch - 6ms/step
Epoch 178/250
141/141 - 1s - loss: 0.0719 - categorical_accuracy: 0.9755 - val_loss: 0.2713 - val_categorical_accuracy: 0.9254 - 875ms/epoch - 6ms/step
Epoch 179/250
141/141 - 1s - loss: 0.1346 - categorical_accuracy: 0.9603 - val_loss: 0.1371 - val_categorical_accuracy: 0.9582 - 862ms/epoch - 6ms/step
Epoch 180/250
141/141 - 1s - loss: 0.0817 - categorical_accuracy: 0.9727 - val_loss: 0.1472 - val_categorical_accuracy: 0.9549 - 860ms/epoch - 6ms/step
Epoch 181/250
141/141 - 1s - loss: 0.0710 - categorical_accuracy: 0.9757 - val_loss: 0.1546 - val_categorical_accuracy: 0.9560 - 862ms/epoch - 6ms/step
Epoch 182/250
141/141 - 1s - loss: 0.0751 - categorical_accuracy: 0.9743 - val_loss: 0.1535 - val_categorical_accuracy: 0.9534 - 861ms/epoch - 6ms/step
Epoch 183/250
141/141 - 1s - loss: 0.0955 - categorical_accuracy: 0.9689 - val_loss: 0.1423 - val_categorical_accuracy: 0.9570 - 871ms/epoch - 6ms/step
Epoch 184/250
141/141 - 1s - loss: 0.0719 - categorical_accuracy: 0.9753 - val_loss: 0.1475 - val_categorical_accuracy: 0.9557 - 858ms/epoch - 6ms/step
Epoch 185/250
141/141 - 1s - loss: 0.0871 - categorical_accuracy: 0.9712 - val_loss: 0.1517 - val_categorical_accuracy: 0.9538 - 876ms/epoch - 6ms/step
Epoch 186/250
141/141 - 1s - loss: 0.0744 - categorical_accuracy: 0.9746 - val_loss: 0.1634 - val_categorical_accuracy: 0.9492 - 877ms/epoch - 6ms/step
Epoch 187/250
141/141 - 1s - loss: 0.0910 - categorical_accuracy: 0.9705 - val_loss: 0.1502 - val_categorical_accuracy: 0.9535 - 874ms/epoch - 6ms/step
Epoch 188/250
141/141 - 1s - loss: 0.0696 - categorical_accuracy: 0.9764 - val_loss: 0.1534 - val_categorical_accuracy: 0.9553 - 858ms/epoch - 6ms/step
Epoch 189/250
Epoch 190/250
141/141 - 1s - loss: 0.0991 - categorical_accuracy: 0.9684 - val_loss: 0.1675 - val_categorical_accuracy: 0.9487 - 877ms/epoch - 6ms/step
Epoch 191/250
141/141 - 1s - loss: 0.0720 - categorical_accuracy: 0.9754 - val_loss: 0.1520 - val_categorical_accuracy: 0.9535 - 888ms/epoch - 6ms/step
Epoch 192/250
141/141 - 1s - loss: 0.0711 - categorical_accuracy: 0.9756 - val_loss: 0.1500 - val_categorical_accuracy: 0.9543 - 863ms/epoch - 6ms/step
Epoch 193/250
141/141 - 1s - loss: 0.0716 - categorical_accuracy: 0.9757 - val_loss: 0.1433 - val_categorical_accuracy: 0.9591 - 878ms/epoch - 6ms/step
Epoch 194/250
141/141 - 1s - loss: 0.1042 - categorical_accuracy: 0.9681 - val_loss: 0.1527 - val_categorical_accuracy: 0.9535 - 877ms/epoch - 6ms/step
Epoch 195/250
141/141 - 1s - loss: 0.0750 - categorical_accuracy: 0.9743 - val_loss: 0.1529 - val_categorical_accuracy: 0.9542 - 875ms/epoch - 6ms/step
Epoch 196/250
141/141 - 1s - loss: 0.0695 - categorical_accuracy: 0.9760 - val_loss: 0.1525 - val_categorical_accuracy: 0.9535 - 857ms/epoch - 6ms/step
Epoch 197/250
141/141 - 1s - loss: 0.0686 - categorical_accuracy: 0.9765 - val_loss: 0.2212 - val_categorical_accuracy: 0.9377 - 861ms/epoch - 6ms/step
Epoch 198/250
141/141 - 1s - loss: 0.3355 - categorical_accuracy: 0.9039 - val_loss: 0.1610 - val_categorical_accuracy: 0.9492 - 873ms/epoch - 6ms/step
Epoch 199/250
141/141 - 1s - loss: 0.0796 - categorical_accuracy: 0.9730 - val_loss: 0.1513 - val_categorical_accuracy: 0.9549 - 878ms/epoch - 6ms/step
Epoch 200/250
141/141 - 1s - loss: 0.0731 - categorical_accuracy: 0.9751 - val_loss: 0.1555 - val_categorical_accuracy: 0.9552 - 839ms/epoch - 6ms/step
Epoch 201/250
141/141 - 1s - loss: 0.0702 - categorical_accuracy: 0.9760 - val_loss: 0.1642 - val_categorical_accuracy: 0.9539 - 868ms/epoch - 6ms/step
Epoch 202/250
141/141 - 1s - loss: 0.0745 - categorical_accuracy: 0.9743 - val_loss: 0.1559 - val_categorical_accuracy: 0.9536 - 886ms/epoch - 6ms/step
Epoch 203/250
141/141 - 1s - loss: 0.0986 - categorical_accuracy: 0.9680 - val_loss: 0.1517 - val_categorical_accuracy: 0.9543 - 873ms/epoch - 6ms/step
Epoch 204/250
141/141 - 1s - loss: 0.0669 - categorical_accuracy: 0.9772 - val_loss: 0.1456 - val_categorical_accuracy: 0.9581 - 861ms/epoch - 6ms/step
Epoch 205/250
141/141 - 1s - loss: 0.0662 - categorical_accuracy: 0.9775 - val_loss: 0.1709 - val_categorical_accuracy: 0.9534 - 861ms/epoch - 6ms/step
Epoch 206/250
141/141 - 1s - loss: 0.0700 - categorical_accuracy: 0.9756 - val_loss: 0.2238 - val_categorical_accuracy: 0.9354 - 878ms/epoch - 6ms/step
Epoch 207/250
141/141 - 1s - loss: 0.1086 - categorical_accuracy: 0.9667 - val_loss: 0.1623 - val_categorical_accuracy: 0.9507 - 886ms/epoch - 6ms/step
Epoch 208/250
141/141 - 1s - loss: 0.0657 - categorical_accuracy: 0.9775 - val_loss: 0.1609 - val_categorical_accuracy: 0.9556 - 860ms/epoch - 6ms/step
Epoch 209/250
141/141 - 1s - loss: 0.0692 - categorical_accuracy: 0.9761 - val_loss: 0.1356 - val_categorical_accuracy: 0.9597 - 875ms/epoch - 6ms/step
Epoch 210/250
141/141 - 1s - loss: 0.0999 - categorical_accuracy: 0.9681 - val_loss: 0.1576 - val_categorical_accuracy: 0.9558 - 877ms/epoch - 6ms/step
Epoch 211/250
141/141 - 1s - loss: 0.0658 - categorical_accuracy: 0.9774 - val_loss: 0.1625 - val_categorical_accuracy: 0.9519 - 871ms/epoch - 6ms/step
Epoch 212/250
141/141 - 1s - loss: 0.0642 - categorical_accuracy: 0.9777 - val_loss: 0.1530 - val_categorical_accuracy: 0.9549 - 862ms/epoch - 6ms/step
Epoch 213/250
141/141 - 1s - loss: 0.0639 - categorical_accuracy: 0.9781 - val_loss: 0.1495 - val_categorical_accuracy: 0.9565 - 864ms/epoch - 6ms/step
Epoch 214/250
141/141 - 1s - loss: 0.0950 - categorical_accuracy: 0.9703 - val_loss: 0.1494 - val_categorical_accuracy: 0.9553 - 858ms/epoch - 6ms/step
Epoch 215/250
141/141 - 1s - loss: 0.0974 - categorical_accuracy: 0.9692 - val_loss: 0.1538 - val_categorical_accuracy: 0.9552 - 860ms/epoch - 6ms/step
Epoch 216/250
141/141 - 1s - loss: 0.0653 - categorical_accuracy: 0.9777 - val_loss: 0.1518 - val_categorical_accuracy: 0.9558 - 859ms/epoch - 6ms/step
Epoch 217/250
141/141 - 1s - loss: 0.0653 - categorical_accuracy: 0.9773 - val_loss: 0.1657 - val_categorical_accuracy: 0.9514 - 876ms/epoch - 6ms/step
Epoch 218/250
141/141 - 1s - loss: 0.0903 - categorical_accuracy: 0.9699 - val_loss: 0.1405 - val_categorical_accuracy: 0.9589 - 878ms/epoch - 6ms/step
Epoch 219/250
141/141 - 1s - loss: 0.0648 - categorical_accuracy: 0.9779 - val_loss: 0.1514 - val_categorical_accuracy: 0.9567 - 876ms/epoch - 6ms/step
Epoch 220/250
141/141 - 1s - loss: 0.0627 - categorical_accuracy: 0.9787 - val_loss: 0.1529 - val_categorical_accuracy: 0.9576 - 859ms/epoch - 6ms/step
Epoch 221/250
141/141 - 1s - loss: 0.0884 - categorical_accuracy: 0.9717 - val_loss: 0.1584 - val_categorical_accuracy: 0.9521 - 859ms/epoch - 6ms/step
Epoch 222/250
141/141 - 1s - loss: 0.0634 - categorical_accuracy: 0.9783 - val_loss: 0.1730 - val_categorical_accuracy: 0.9470 - 878ms/epoch - 6ms/step
Epoch 223/250
141/141 - 1s - loss: 0.0643 - categorical_accuracy: 0.9779 - val_loss: 0.1808 - val_categorical_accuracy: 0.9476 - 861ms/epoch - 6ms/step
Epoch 224/250
141/141 - 1s - loss: 0.0643 - categorical_accuracy: 0.9776 - val_loss: 0.1497 - val_categorical_accuracy: 0.9585 - 858ms/epoch - 6ms/step
Epoch 225/250
141/141 - 1s - loss: 0.0795 - categorical_accuracy: 0.9736 - val_loss: 0.1741 - val_categorical_accuracy: 0.9487 - 876ms/epoch - 6ms/step
Epoch 226/250
141/141 - 1s - loss: 0.0928 - categorical_accuracy: 0.9701 - val_loss: 0.1425 - val_categorical_accuracy: 0.9582 - 878ms/epoch - 6ms/step
Epoch 227/250
141/141 - 1s - loss: 0.0704 - categorical_accuracy: 0.9763 - val_loss: 0.1437 - val_categorical_accuracy: 0.9585 - 860ms/epoch - 6ms/step
Epoch 228/250
141/141 - 1s - loss: 0.0627 - categorical_accuracy: 0.9786 - val_loss: 0.1454 - val_categorical_accuracy: 0.9591 - 859ms/epoch - 6ms/step
Epoch 229/250
141/141 - 1s - loss: 0.0615 - categorical_accuracy: 0.9788 - val_loss: 0.1476 - val_categorical_accuracy: 0.9560 - 860ms/epoch - 6ms/step
Epoch 230/250
141/141 - 1s - loss: 0.0934 - categorical_accuracy: 0.9703 - val_loss: 0.1497 - val_categorical_accuracy: 0.9553 - 860ms/epoch - 6ms/step
Epoch 231/250
141/141 - 1s - loss: 0.0632 - categorical_accuracy: 0.9785 - val_loss: 0.1536 - val_categorical_accuracy: 0.9568 - 878ms/epoch - 6ms/step
Epoch 232/250
141/141 - 1s - loss: 0.0636 - categorical_accuracy: 0.9780 - val_loss: 0.1492 - val_categorical_accuracy: 0.9579 - 862ms/epoch - 6ms/step
Epoch 233/250
141/141 - 1s - loss: 0.0610 - categorical_accuracy: 0.9790 - val_loss: 0.1512 - val_categorical_accuracy: 0.9547 - 858ms/epoch - 6ms/step
Epoch 234/250
141/141 - 1s - loss: 0.0647 - categorical_accuracy: 0.9777 - val_loss: 0.1411 - val_categorical_accuracy: 0.9601 - 873ms/epoch - 6ms/step
Epoch 235/250
141/141 - 1s - loss: 0.0620 - categorical_accuracy: 0.9787 - val_loss: 0.1510 - val_categorical_accuracy: 0.9587 - 892ms/epoch - 6ms/step
Epoch 236/250
141/141 - 1s - loss: 0.1721 - categorical_accuracy: 0.9521 - val_loss: 0.1506 - val_categorical_accuracy: 0.9552 - 863ms/epoch - 6ms/step
Epoch 237/250
141/141 - 1s - loss: 0.0620 - categorical_accuracy: 0.9788 - val_loss: 0.1508 - val_categorical_accuracy: 0.9559 - 877ms/epoch - 6ms/step
Epoch 238/250
141/141 - 1s - loss: 0.0605 - categorical_accuracy: 0.9790 - val_loss: 0.1555 - val_categorical_accuracy: 0.9575 - 877ms/epoch - 6ms/step
Epoch 239/250
141/141 - 1s - loss: 0.0970 - categorical_accuracy: 0.9705 - val_loss: 0.1942 - val_categorical_accuracy: 0.9349 - 859ms/epoch - 6ms/step
Epoch 240/250
141/141 - 1s - loss: 0.0649 - categorical_accuracy: 0.9780 - val_loss: 0.1489 - val_categorical_accuracy: 0.9566 - 862ms/epoch - 6ms/step
Epoch 241/250
141/141 - 1s - loss: 0.0601 - categorical_accuracy: 0.9792 - val_loss: 0.1759 - val_categorical_accuracy: 0.9479 - 860ms/epoch - 6ms/step
Epoch 242/250
141/141 - 1s - loss: 0.0946 - categorical_accuracy: 0.9705 - val_loss: 0.1362 - val_categorical_accuracy: 0.9613 - 890ms/epoch - 6ms/step
Epoch 243/250
141/141 - 1s - loss: 0.0600 - categorical_accuracy: 0.9796 - val_loss: 0.1477 - val_categorical_accuracy: 0.9594 - 873ms/epoch - 6ms/step
Epoch 244/250
141/141 - 1s - loss: 0.0879 - categorical_accuracy: 0.9718 - val_loss: 0.1510 - val_categorical_accuracy: 0.9570 - 843ms/epoch - 6ms/step
Epoch 245/250
141/141 - 1s - loss: 0.0627 - categorical_accuracy: 0.9785 - val_loss: 0.3301 - val_categorical_accuracy: 0.9121 - 859ms/epoch - 6ms/step
Epoch 246/250
141/141 - 1s - loss: 0.0816 - categorical_accuracy: 0.9734 - val_loss: 0.1566 - val_categorical_accuracy: 0.9519 - 878ms/epoch - 6ms/step
Epoch 247/250
141/141 - 1s - loss: 0.0598 - categorical_accuracy: 0.9794 - val_loss: 0.1416 - val_categorical_accuracy: 0.9614 - 863ms/epoch - 6ms/step
Epoch 248/250
141/141 - 1s - loss: 0.0892 - categorical_accuracy: 0.9718 - val_loss: 0.1405 - val_categorical_accuracy: 0.9604 - 861ms/epoch - 6ms/step
Epoch 249/250
141/141 - 1s - loss: 0.0586 - categorical_accuracy: 0.9799 - val_loss: 0.1630 - val_categorical_accuracy: 0.9523 - 878ms/epoch - 6ms/step
Epoch 250/250
141/141 - 1s - loss: 0.0583 - categorical_accuracy: 0.9799 - val_loss: 0.1507 - val_categorical_accuracy: 0.9578 - 871ms/epoch - 6ms/step
processing fold # 3 
Epoch 1/250
141/141 - 2s - loss: 1.9471 - categorical_accuracy: 0.2723 - val_loss: 1.6574 - val_categorical_accuracy: 0.3879 - 2s/epoch - 12ms/step
Epoch 2/250
141/141 - 1s - loss: 1.5439 - categorical_accuracy: 0.4144 - val_loss: 1.4824 - val_categorical_accuracy: 0.4294 - 882ms/epoch - 6ms/step
Epoch 3/250
141/141 - 1s - loss: 1.2996 - categorical_accuracy: 0.5034 - val_loss: 1.2358 - val_categorical_accuracy: 0.5154 - 855ms/epoch - 6ms/step
Epoch 4/250
141/141 - 1s - loss: 1.2294 - categorical_accuracy: 0.5397 - val_loss: 1.0310 - val_categorical_accuracy: 0.6196 - 874ms/epoch - 6ms/step
Epoch 5/250
141/141 - 1s - loss: 1.0376 - categorical_accuracy: 0.6073 - val_loss: 1.0421 - val_categorical_accuracy: 0.6017 - 845ms/epoch - 6ms/step
Epoch 6/250
141/141 - 1s - loss: 0.9284 - categorical_accuracy: 0.6529 - val_loss: 0.8228 - val_categorical_accuracy: 0.6871 - 854ms/epoch - 6ms/step
Epoch 7/250
141/141 - 1s - loss: 0.8406 - categorical_accuracy: 0.6858 - val_loss: 0.8061 - val_categorical_accuracy: 0.6951 - 843ms/epoch - 6ms/step
Epoch 8/250
141/141 - 1s - loss: 0.8284 - categorical_accuracy: 0.6980 - val_loss: 0.7659 - val_categorical_accuracy: 0.7123 - 858ms/epoch - 6ms/step
Epoch 9/250
141/141 - 1s - loss: 0.7385 - categorical_accuracy: 0.7266 - val_loss: 0.6622 - val_categorical_accuracy: 0.7520 - 861ms/epoch - 6ms/step
Epoch 10/250
141/141 - 1s - loss: 0.7206 - categorical_accuracy: 0.7382 - val_loss: 0.7128 - val_categorical_accuracy: 0.7306 - 863ms/epoch - 6ms/step
Epoch 11/250
141/141 - 1s - loss: 0.6285 - categorical_accuracy: 0.7635 - val_loss: 1.6483 - val_categorical_accuracy: 0.5629 - 858ms/epoch - 6ms/step
Epoch 12/250
141/141 - 1s - loss: 0.6376 - categorical_accuracy: 0.7682 - val_loss: 0.5738 - val_categorical_accuracy: 0.7792 - 876ms/epoch - 6ms/step
Epoch 13/250
141/141 - 1s - loss: 0.6118 - categorical_accuracy: 0.7776 - val_loss: 0.5916 - val_categorical_accuracy: 0.7723 - 846ms/epoch - 6ms/step
Epoch 14/250
141/141 - 1s - loss: 0.5296 - categorical_accuracy: 0.8012 - val_loss: 0.5405 - val_categorical_accuracy: 0.7936 - 859ms/epoch - 6ms/step
Epoch 15/250
141/141 - 1s - loss: 0.6703 - categorical_accuracy: 0.7670 - val_loss: 0.4897 - val_categorical_accuracy: 0.8180 - 885ms/epoch - 6ms/step
Epoch 16/250
141/141 - 1s - loss: 0.5012 - categorical_accuracy: 0.8163 - val_loss: 0.5688 - val_categorical_accuracy: 0.7944 - 874ms/epoch - 6ms/step
Epoch 17/250
141/141 - 1s - loss: 0.4666 - categorical_accuracy: 0.8271 - val_loss: 0.4649 - val_categorical_accuracy: 0.8309 - 860ms/epoch - 6ms/step
Epoch 18/250
141/141 - 1s - loss: 0.6144 - categorical_accuracy: 0.7958 - val_loss: 0.4456 - val_categorical_accuracy: 0.8325 - 878ms/epoch - 6ms/step
Epoch 19/250
141/141 - 1s - loss: 0.4431 - categorical_accuracy: 0.8379 - val_loss: 0.4316 - val_categorical_accuracy: 0.8374 - 876ms/epoch - 6ms/step
Epoch 20/250
141/141 - 1s - loss: 0.4139 - categorical_accuracy: 0.8472 - val_loss: 0.4263 - val_categorical_accuracy: 0.8383 - 892ms/epoch - 6ms/step
Epoch 21/250
141/141 - 1s - loss: 0.5044 - categorical_accuracy: 0.8296 - val_loss: 0.3571 - val_categorical_accuracy: 0.8695 - 879ms/epoch - 6ms/step
Epoch 22/250
141/141 - 1s - loss: 0.3876 - categorical_accuracy: 0.8588 - val_loss: 0.3588 - val_categorical_accuracy: 0.8689 - 855ms/epoch - 6ms/step
Epoch 23/250
141/141 - 1s - loss: 0.3794 - categorical_accuracy: 0.8621 - val_loss: 0.3499 - val_categorical_accuracy: 0.8701 - 860ms/epoch - 6ms/step
Epoch 24/250
141/141 - 1s - loss: 0.4388 - categorical_accuracy: 0.8486 - val_loss: 0.6071 - val_categorical_accuracy: 0.7965 - 879ms/epoch - 6ms/step
Epoch 25/250
141/141 - 1s - loss: 0.3545 - categorical_accuracy: 0.8738 - val_loss: 0.4160 - val_categorical_accuracy: 0.8472 - 874ms/epoch - 6ms/step
Epoch 26/250
141/141 - 1s - loss: 0.3376 - categorical_accuracy: 0.8774 - val_loss: 0.3678 - val_categorical_accuracy: 0.8616 - 857ms/epoch - 6ms/step
Epoch 27/250
141/141 - 1s - loss: 0.3340 - categorical_accuracy: 0.8786 - val_loss: 0.3417 - val_categorical_accuracy: 0.8796 - 872ms/epoch - 6ms/step
Epoch 28/250
141/141 - 1s - loss: 0.3546 - categorical_accuracy: 0.8745 - val_loss: 0.2986 - val_categorical_accuracy: 0.8939 - 867ms/epoch - 6ms/step
Epoch 29/250
141/141 - 1s - loss: 0.3168 - categorical_accuracy: 0.8860 - val_loss: 0.3196 - val_categorical_accuracy: 0.8820 - 871ms/epoch - 6ms/step
Epoch 30/250
141/141 - 1s - loss: 0.3020 - categorical_accuracy: 0.8902 - val_loss: 0.2880 - val_categorical_accuracy: 0.8996 - 854ms/epoch - 6ms/step
Epoch 31/250
141/141 - 1s - loss: 0.3092 - categorical_accuracy: 0.8896 - val_loss: 0.3071 - val_categorical_accuracy: 0.8897 - 870ms/epoch - 6ms/step
Epoch 32/250
141/141 - 1s - loss: 0.4943 - categorical_accuracy: 0.8438 - val_loss: 0.3262 - val_categorical_accuracy: 0.8814 - 875ms/epoch - 6ms/step
Epoch 33/250
141/141 - 1s - loss: 0.3255 - categorical_accuracy: 0.8867 - val_loss: 0.2960 - val_categorical_accuracy: 0.8926 - 877ms/epoch - 6ms/step
Epoch 34/250
141/141 - 1s - loss: 0.2777 - categorical_accuracy: 0.9004 - val_loss: 0.3360 - val_categorical_accuracy: 0.8760 - 878ms/epoch - 6ms/step
Epoch 35/250
141/141 - 1s - loss: 0.2669 - categorical_accuracy: 0.9042 - val_loss: 0.4939 - val_categorical_accuracy: 0.8289 - 860ms/epoch - 6ms/step
Epoch 36/250
141/141 - 1s - loss: 0.2865 - categorical_accuracy: 0.8976 - val_loss: 0.2975 - val_categorical_accuracy: 0.8900 - 868ms/epoch - 6ms/step
Epoch 37/250
141/141 - 1s - loss: 0.2620 - categorical_accuracy: 0.9064 - val_loss: 0.2530 - val_categorical_accuracy: 0.9111 - 868ms/epoch - 6ms/step
Epoch 38/250
141/141 - 1s - loss: 0.2612 - categorical_accuracy: 0.9070 - val_loss: 0.2612 - val_categorical_accuracy: 0.9068 - 869ms/epoch - 6ms/step
Epoch 39/250
141/141 - 1s - loss: 0.2431 - categorical_accuracy: 0.9134 - val_loss: 0.2772 - val_categorical_accuracy: 0.8988 - 871ms/epoch - 6ms/step
Epoch 40/250
141/141 - 1s - loss: 0.2919 - categorical_accuracy: 0.8994 - val_loss: 0.2538 - val_categorical_accuracy: 0.9124 - 870ms/epoch - 6ms/step
Epoch 41/250
141/141 - 1s - loss: 0.2489 - categorical_accuracy: 0.9140 - val_loss: 0.2810 - val_categorical_accuracy: 0.9002 - 860ms/epoch - 6ms/step
Epoch 42/250
141/141 - 1s - loss: 0.2497 - categorical_accuracy: 0.9117 - val_loss: 0.2818 - val_categorical_accuracy: 0.8985 - 878ms/epoch - 6ms/step
Epoch 43/250
141/141 - 1s - loss: 0.2278 - categorical_accuracy: 0.9194 - val_loss: 0.2286 - val_categorical_accuracy: 0.9176 - 861ms/epoch - 6ms/step
Epoch 44/250
141/141 - 1s - loss: 0.2291 - categorical_accuracy: 0.9189 - val_loss: 0.2506 - val_categorical_accuracy: 0.9098 - 877ms/epoch - 6ms/step
Epoch 45/250
141/141 - 1s - loss: 0.2211 - categorical_accuracy: 0.9214 - val_loss: 0.2331 - val_categorical_accuracy: 0.9174 - 857ms/epoch - 6ms/step
Epoch 46/250
141/141 - 1s - loss: 0.3061 - categorical_accuracy: 0.9001 - val_loss: 0.2522 - val_categorical_accuracy: 0.9121 - 861ms/epoch - 6ms/step
Epoch 47/250
141/141 - 1s - loss: 0.2152 - categorical_accuracy: 0.9242 - val_loss: 0.2538 - val_categorical_accuracy: 0.9086 - 860ms/epoch - 6ms/step
Epoch 48/250
141/141 - 1s - loss: 0.2165 - categorical_accuracy: 0.9245 - val_loss: 0.2202 - val_categorical_accuracy: 0.9245 - 844ms/epoch - 6ms/step
Epoch 49/250
141/141 - 1s - loss: 0.2141 - categorical_accuracy: 0.9243 - val_loss: 0.2378 - val_categorical_accuracy: 0.9162 - 874ms/epoch - 6ms/step
Epoch 50/250
141/141 - 1s - loss: 0.2520 - categorical_accuracy: 0.9164 - val_loss: 0.2411 - val_categorical_accuracy: 0.9169 - 858ms/epoch - 6ms/step
Epoch 51/250
141/141 - 1s - loss: 0.2688 - categorical_accuracy: 0.9126 - val_loss: 0.2133 - val_categorical_accuracy: 0.9264 - 877ms/epoch - 6ms/step
Epoch 52/250
141/141 - 1s - loss: 0.1996 - categorical_accuracy: 0.9297 - val_loss: 0.2296 - val_categorical_accuracy: 0.9194 - 861ms/epoch - 6ms/step
Epoch 53/250
141/141 - 1s - loss: 0.1959 - categorical_accuracy: 0.9306 - val_loss: 0.2222 - val_categorical_accuracy: 0.9205 - 876ms/epoch - 6ms/step
Epoch 54/250
141/141 - 1s - loss: 0.1936 - categorical_accuracy: 0.9323 - val_loss: 0.1992 - val_categorical_accuracy: 0.9313 - 876ms/epoch - 6ms/step
Epoch 55/250
141/141 - 1s - loss: 0.2260 - categorical_accuracy: 0.9260 - val_loss: 0.2156 - val_categorical_accuracy: 0.9242 - 895ms/epoch - 6ms/step
Epoch 56/250
141/141 - 1s - loss: 0.1882 - categorical_accuracy: 0.9346 - val_loss: 0.2229 - val_categorical_accuracy: 0.9218 - 1s/epoch - 8ms/step
Epoch 57/250
141/141 - 1s - loss: 0.1891 - categorical_accuracy: 0.9340 - val_loss: 0.2472 - val_categorical_accuracy: 0.9124 - 877ms/epoch - 6ms/step
Epoch 58/250
141/141 - 1s - loss: 0.2851 - categorical_accuracy: 0.9125 - val_loss: 0.2434 - val_categorical_accuracy: 0.9094 - 860ms/epoch - 6ms/step
Epoch 59/250
141/141 - 1s - loss: 0.1766 - categorical_accuracy: 0.9387 - val_loss: 0.1895 - val_categorical_accuracy: 0.9376 - 861ms/epoch - 6ms/step
Epoch 60/250
141/141 - 1s - loss: 0.1795 - categorical_accuracy: 0.9371 - val_loss: 0.2412 - val_categorical_accuracy: 0.9159 - 876ms/epoch - 6ms/step
Epoch 61/250
141/141 - 1s - loss: 0.1778 - categorical_accuracy: 0.9379 - val_loss: 0.2012 - val_categorical_accuracy: 0.9302 - 861ms/epoch - 6ms/step
Epoch 62/250
141/141 - 1s - loss: 0.1734 - categorical_accuracy: 0.9394 - val_loss: 0.3824 - val_categorical_accuracy: 0.8696 - 842ms/epoch - 6ms/step
Epoch 63/250
141/141 - 1s - loss: 0.1719 - categorical_accuracy: 0.9400 - val_loss: 0.2094 - val_categorical_accuracy: 0.9277 - 874ms/epoch - 6ms/step
Epoch 64/250
141/141 - 1s - loss: 0.3113 - categorical_accuracy: 0.9071 - val_loss: 0.2054 - val_categorical_accuracy: 0.9294 - 862ms/epoch - 6ms/step
Epoch 65/250
141/141 - 1s - loss: 0.1712 - categorical_accuracy: 0.9409 - val_loss: 0.1760 - val_categorical_accuracy: 0.9403 - 860ms/epoch - 6ms/step
Epoch 66/250
141/141 - 1s - loss: 0.1648 - categorical_accuracy: 0.9428 - val_loss: 0.2057 - val_categorical_accuracy: 0.9299 - 843ms/epoch - 6ms/step
Epoch 67/250
141/141 - 1s - loss: 0.1629 - categorical_accuracy: 0.9439 - val_loss: 0.2180 - val_categorical_accuracy: 0.9268 - 877ms/epoch - 6ms/step
Epoch 68/250
141/141 - 1s - loss: 0.1690 - categorical_accuracy: 0.9413 - val_loss: 0.1929 - val_categorical_accuracy: 0.9338 - 875ms/epoch - 6ms/step
Epoch 69/250
141/141 - 1s - loss: 0.1554 - categorical_accuracy: 0.9460 - val_loss: 0.1819 - val_categorical_accuracy: 0.9388 - 875ms/epoch - 6ms/step
Epoch 70/250
141/141 - 1s - loss: 0.2031 - categorical_accuracy: 0.9338 - val_loss: 0.1843 - val_categorical_accuracy: 0.9377 - 845ms/epoch - 6ms/step
Epoch 71/250
141/141 - 1s - loss: 0.1568 - categorical_accuracy: 0.9458 - val_loss: 0.2050 - val_categorical_accuracy: 0.9297 - 877ms/epoch - 6ms/step
Epoch 72/250
141/141 - 1s - loss: 0.1608 - categorical_accuracy: 0.9454 - val_loss: 0.2106 - val_categorical_accuracy: 0.9271 - 844ms/epoch - 6ms/step
Epoch 73/250
141/141 - 1s - loss: 0.1608 - categorical_accuracy: 0.9452 - val_loss: 0.1913 - val_categorical_accuracy: 0.9339 - 856ms/epoch - 6ms/step
Epoch 74/250
141/141 - 1s - loss: 0.1482 - categorical_accuracy: 0.9487 - val_loss: 0.3603 - val_categorical_accuracy: 0.8840 - 874ms/epoch - 6ms/step
Epoch 75/250
141/141 - 1s - loss: 0.1656 - categorical_accuracy: 0.9438 - val_loss: 0.1767 - val_categorical_accuracy: 0.9400 - 886ms/epoch - 6ms/step
Epoch 76/250
141/141 - 1s - loss: 0.1496 - categorical_accuracy: 0.9492 - val_loss: 0.1644 - val_categorical_accuracy: 0.9451 - 870ms/epoch - 6ms/step
Epoch 77/250
141/141 - 1s - loss: 0.1508 - categorical_accuracy: 0.9479 - val_loss: 0.6639 - val_categorical_accuracy: 0.8239 - 859ms/epoch - 6ms/step
Epoch 78/250
141/141 - 1s - loss: 0.2001 - categorical_accuracy: 0.9369 - val_loss: 0.2145 - val_categorical_accuracy: 0.9270 - 878ms/epoch - 6ms/step
Epoch 79/250
141/141 - 1s - loss: 0.1437 - categorical_accuracy: 0.9498 - val_loss: 0.2686 - val_categorical_accuracy: 0.9110 - 860ms/epoch - 6ms/step
Epoch 80/250
141/141 - 1s - loss: 0.1348 - categorical_accuracy: 0.9539 - val_loss: 0.2230 - val_categorical_accuracy: 0.9193 - 859ms/epoch - 6ms/step
Epoch 81/250
141/141 - 1s - loss: 0.1529 - categorical_accuracy: 0.9475 - val_loss: 0.1827 - val_categorical_accuracy: 0.9388 - 861ms/epoch - 6ms/step
Epoch 82/250
141/141 - 1s - loss: 0.1323 - categorical_accuracy: 0.9542 - val_loss: 0.1838 - val_categorical_accuracy: 0.9387 - 862ms/epoch - 6ms/step
Epoch 83/250
141/141 - 1s - loss: 0.1518 - categorical_accuracy: 0.9478 - val_loss: 0.1619 - val_categorical_accuracy: 0.9461 - 874ms/epoch - 6ms/step
Epoch 84/250
141/141 - 1s - loss: 0.1322 - categorical_accuracy: 0.9546 - val_loss: 0.1772 - val_categorical_accuracy: 0.9405 - 861ms/epoch - 6ms/step
Epoch 85/250
141/141 - 1s - loss: 0.2066 - categorical_accuracy: 0.9368 - val_loss: 0.3045 - val_categorical_accuracy: 0.8952 - 873ms/epoch - 6ms/step
Epoch 86/250
141/141 - 1s - loss: 0.1389 - categorical_accuracy: 0.9530 - val_loss: 0.2056 - val_categorical_accuracy: 0.9303 - 861ms/epoch - 6ms/step
Epoch 87/250
141/141 - 1s - loss: 0.1432 - categorical_accuracy: 0.9510 - val_loss: 0.1731 - val_categorical_accuracy: 0.9421 - 876ms/epoch - 6ms/step
Epoch 88/250
141/141 - 1s - loss: 0.1241 - categorical_accuracy: 0.9574 - val_loss: 0.1656 - val_categorical_accuracy: 0.9443 - 861ms/epoch - 6ms/step
Epoch 89/250
141/141 - 1s - loss: 0.1348 - categorical_accuracy: 0.9533 - val_loss: 0.2071 - val_categorical_accuracy: 0.9270 - 876ms/epoch - 6ms/step
Epoch 90/250
141/141 - 1s - loss: 0.1270 - categorical_accuracy: 0.9564 - val_loss: 0.1815 - val_categorical_accuracy: 0.9397 - 843ms/epoch - 6ms/step
Epoch 91/250
141/141 - 1s - loss: 0.1365 - categorical_accuracy: 0.9525 - val_loss: 0.1618 - val_categorical_accuracy: 0.9451 - 861ms/epoch - 6ms/step
Epoch 92/250
141/141 - 1s - loss: 0.1237 - categorical_accuracy: 0.9570 - val_loss: 0.1738 - val_categorical_accuracy: 0.9420 - 862ms/epoch - 6ms/step
Epoch 93/250
141/141 - 1s - loss: 0.1721 - categorical_accuracy: 0.9466 - val_loss: 0.1611 - val_categorical_accuracy: 0.9461 - 877ms/epoch - 6ms/step
Epoch 94/250
141/141 - 1s - loss: 0.1304 - categorical_accuracy: 0.9557 - val_loss: 0.1618 - val_categorical_accuracy: 0.9450 - 861ms/epoch - 6ms/step
Epoch 95/250
141/141 - 1s - loss: 0.1134 - categorical_accuracy: 0.9611 - val_loss: 0.1871 - val_categorical_accuracy: 0.9345 - 888ms/epoch - 6ms/step
Epoch 96/250
141/141 - 1s - loss: 0.1242 - categorical_accuracy: 0.9571 - val_loss: 0.1477 - val_categorical_accuracy: 0.9525 - 893ms/epoch - 6ms/step
Epoch 97/250
141/141 - 1s - loss: 0.1404 - categorical_accuracy: 0.9539 - val_loss: 0.1723 - val_categorical_accuracy: 0.9421 - 873ms/epoch - 6ms/step
Epoch 98/250
141/141 - 1s - loss: 0.1212 - categorical_accuracy: 0.9578 - val_loss: 0.1753 - val_categorical_accuracy: 0.9399 - 860ms/epoch - 6ms/step
Epoch 99/250
141/141 - 1s - loss: 0.1291 - categorical_accuracy: 0.9558 - val_loss: 0.1563 - val_categorical_accuracy: 0.9493 - 862ms/epoch - 6ms/step
Epoch 100/250
Epoch 101/250
141/141 - 1s - loss: 0.1314 - categorical_accuracy: 0.9552 - val_loss: 0.1693 - val_categorical_accuracy: 0.9425 - 877ms/epoch - 6ms/step
Epoch 102/250
141/141 - 1s - loss: 0.1245 - categorical_accuracy: 0.9575 - val_loss: 0.1597 - val_categorical_accuracy: 0.9460 - 860ms/epoch - 6ms/step
Epoch 103/250
141/141 - 1s - loss: 0.1100 - categorical_accuracy: 0.9621 - val_loss: 0.2028 - val_categorical_accuracy: 0.9337 - 894ms/epoch - 6ms/step
Epoch 104/250
141/141 - 1s - loss: 0.1465 - categorical_accuracy: 0.9524 - val_loss: 0.1796 - val_categorical_accuracy: 0.9407 - 873ms/epoch - 6ms/step
Epoch 105/250
141/141 - 1s - loss: 0.1194 - categorical_accuracy: 0.9595 - val_loss: 0.1674 - val_categorical_accuracy: 0.9441 - 870ms/epoch - 6ms/step
Epoch 106/250
141/141 - 1s - loss: 0.1290 - categorical_accuracy: 0.9581 - val_loss: 0.1738 - val_categorical_accuracy: 0.9409 - 857ms/epoch - 6ms/step
Epoch 107/250
141/141 - 1s - loss: 0.1153 - categorical_accuracy: 0.9604 - val_loss: 0.1589 - val_categorical_accuracy: 0.9455 - 877ms/epoch - 6ms/step
Epoch 108/250
141/141 - 1s - loss: 0.1120 - categorical_accuracy: 0.9611 - val_loss: 0.1516 - val_categorical_accuracy: 0.9501 - 862ms/epoch - 6ms/step
Epoch 109/250
141/141 - 1s - loss: 0.1061 - categorical_accuracy: 0.9639 - val_loss: 0.1516 - val_categorical_accuracy: 0.9513 - 872ms/epoch - 6ms/step
Epoch 110/250
141/141 - 1s - loss: 0.1518 - categorical_accuracy: 0.9535 - val_loss: 0.1463 - val_categorical_accuracy: 0.9514 - 860ms/epoch - 6ms/step
Epoch 111/250
141/141 - 1s - loss: 0.1068 - categorical_accuracy: 0.9632 - val_loss: 0.1472 - val_categorical_accuracy: 0.9520 - 874ms/epoch - 6ms/step
Epoch 112/250
141/141 - 1s - loss: 0.1281 - categorical_accuracy: 0.9587 - val_loss: 0.1522 - val_categorical_accuracy: 0.9502 - 872ms/epoch - 6ms/step
Epoch 113/250
141/141 - 1s - loss: 0.1038 - categorical_accuracy: 0.9647 - val_loss: 0.1947 - val_categorical_accuracy: 0.9374 - 861ms/epoch - 6ms/step
Epoch 114/250
141/141 - 1s - loss: 0.1064 - categorical_accuracy: 0.9636 - val_loss: 0.1718 - val_categorical_accuracy: 0.9425 - 856ms/epoch - 6ms/step
Epoch 115/250
141/141 - 1s - loss: 0.1114 - categorical_accuracy: 0.9627 - val_loss: 0.1573 - val_categorical_accuracy: 0.9495 - 853ms/epoch - 6ms/step
Epoch 116/250
141/141 - 1s - loss: 0.1027 - categorical_accuracy: 0.9644 - val_loss: 0.1711 - val_categorical_accuracy: 0.9456 - 867ms/epoch - 6ms/step
Epoch 117/250
141/141 - 1s - loss: 0.2124 - categorical_accuracy: 0.9398 - val_loss: 0.1569 - val_categorical_accuracy: 0.9488 - 876ms/epoch - 6ms/step
Epoch 118/250
141/141 - 1s - loss: 0.0985 - categorical_accuracy: 0.9665 - val_loss: 0.1522 - val_categorical_accuracy: 0.9489 - 850ms/epoch - 6ms/step
Epoch 119/250
141/141 - 1s - loss: 0.1236 - categorical_accuracy: 0.9599 - val_loss: 0.1540 - val_categorical_accuracy: 0.9517 - 861ms/epoch - 6ms/step
Epoch 120/250
141/141 - 1s - loss: 0.1007 - categorical_accuracy: 0.9656 - val_loss: 0.2583 - val_categorical_accuracy: 0.9147 - 856ms/epoch - 6ms/step
Epoch 121/250
141/141 - 1s - loss: 0.1080 - categorical_accuracy: 0.9633 - val_loss: 0.1671 - val_categorical_accuracy: 0.9475 - 860ms/epoch - 6ms/step
Epoch 122/250
141/141 - 1s - loss: 0.0998 - categorical_accuracy: 0.9655 - val_loss: 0.1639 - val_categorical_accuracy: 0.9470 - 879ms/epoch - 6ms/step
Epoch 123/250
141/141 - 1s - loss: 0.1897 - categorical_accuracy: 0.9446 - val_loss: 0.1480 - val_categorical_accuracy: 0.9531 - 894ms/epoch - 6ms/step
Epoch 124/250
141/141 - 1s - loss: 0.0953 - categorical_accuracy: 0.9674 - val_loss: 0.1920 - val_categorical_accuracy: 0.9351 - 877ms/epoch - 6ms/step
Epoch 125/250
141/141 - 1s - loss: 0.0959 - categorical_accuracy: 0.9673 - val_loss: 0.1440 - val_categorical_accuracy: 0.9539 - 874ms/epoch - 6ms/step
Epoch 126/250
141/141 - 1s - loss: 0.1383 - categorical_accuracy: 0.9566 - val_loss: 0.1472 - val_categorical_accuracy: 0.9531 - 857ms/epoch - 6ms/step
Epoch 127/250
141/141 - 1s - loss: 0.0945 - categorical_accuracy: 0.9677 - val_loss: 0.1695 - val_categorical_accuracy: 0.9438 - 858ms/epoch - 6ms/step
Epoch 128/250
141/141 - 1s - loss: 0.0963 - categorical_accuracy: 0.9672 - val_loss: 0.1462 - val_categorical_accuracy: 0.9540 - 874ms/epoch - 6ms/step
Epoch 129/250
141/141 - 1s - loss: 0.1404 - categorical_accuracy: 0.9566 - val_loss: 0.1440 - val_categorical_accuracy: 0.9542 - 878ms/epoch - 6ms/step
Epoch 130/250
141/141 - 1s - loss: 0.0919 - categorical_accuracy: 0.9685 - val_loss: 0.2344 - val_categorical_accuracy: 0.9304 - 844ms/epoch - 6ms/step
Epoch 131/250
141/141 - 1s - loss: 0.0888 - categorical_accuracy: 0.9697 - val_loss: 0.1535 - val_categorical_accuracy: 0.9520 - 861ms/epoch - 6ms/step
Epoch 132/250
141/141 - 1s - loss: 0.1175 - categorical_accuracy: 0.9620 - val_loss: 0.1569 - val_categorical_accuracy: 0.9495 - 876ms/epoch - 6ms/step
Epoch 133/250
141/141 - 1s - loss: 0.0887 - categorical_accuracy: 0.9695 - val_loss: 0.1641 - val_categorical_accuracy: 0.9456 - 875ms/epoch - 6ms/step
Epoch 134/250
141/141 - 1s - loss: 0.1130 - categorical_accuracy: 0.9627 - val_loss: 0.1406 - val_categorical_accuracy: 0.9569 - 859ms/epoch - 6ms/step
Epoch 135/250
141/141 - 1s - loss: 0.0864 - categorical_accuracy: 0.9705 - val_loss: 0.1924 - val_categorical_accuracy: 0.9395 - 875ms/epoch - 6ms/step
Epoch 136/250
141/141 - 1s - loss: 0.1154 - categorical_accuracy: 0.9624 - val_loss: 0.1397 - val_categorical_accuracy: 0.9568 - 877ms/epoch - 6ms/step
Epoch 137/250
141/141 - 1s - loss: 0.0890 - categorical_accuracy: 0.9694 - val_loss: 0.1493 - val_categorical_accuracy: 0.9523 - 862ms/epoch - 6ms/step
Epoch 138/250
141/141 - 1s - loss: 0.0875 - categorical_accuracy: 0.9700 - val_loss: 0.1744 - val_categorical_accuracy: 0.9440 - 847ms/epoch - 6ms/step
Epoch 139/250
141/141 - 1s - loss: 0.1163 - categorical_accuracy: 0.9631 - val_loss: 0.1517 - val_categorical_accuracy: 0.9528 - 858ms/epoch - 6ms/step
Epoch 140/250
141/141 - 1s - loss: 0.0917 - categorical_accuracy: 0.9684 - val_loss: 0.1840 - val_categorical_accuracy: 0.9446 - 878ms/epoch - 6ms/step
Epoch 141/250
141/141 - 1s - loss: 0.0868 - categorical_accuracy: 0.9702 - val_loss: 0.1547 - val_categorical_accuracy: 0.9522 - 861ms/epoch - 6ms/step
Epoch 142/250
141/141 - 1s - loss: 0.1157 - categorical_accuracy: 0.9632 - val_loss: 0.1560 - val_categorical_accuracy: 0.9501 - 856ms/epoch - 6ms/step
Epoch 143/250
141/141 - 1s - loss: 0.1093 - categorical_accuracy: 0.9644 - val_loss: 0.1521 - val_categorical_accuracy: 0.9505 - 876ms/epoch - 6ms/step
Epoch 144/250
141/141 - 1s - loss: 0.0853 - categorical_accuracy: 0.9710 - val_loss: 0.1981 - val_categorical_accuracy: 0.9427 - 861ms/epoch - 6ms/step
Epoch 145/250
141/141 - 1s - loss: 0.1423 - categorical_accuracy: 0.9577 - val_loss: 0.1459 - val_categorical_accuracy: 0.9551 - 846ms/epoch - 6ms/step
Epoch 146/250
141/141 - 1s - loss: 0.0833 - categorical_accuracy: 0.9714 - val_loss: 0.1574 - val_categorical_accuracy: 0.9507 - 864ms/epoch - 6ms/step
Epoch 147/250
141/141 - 1s - loss: 0.0854 - categorical_accuracy: 0.9706 - val_loss: 0.1451 - val_categorical_accuracy: 0.9551 - 875ms/epoch - 6ms/step
Epoch 148/250
141/141 - 1s - loss: 0.1039 - categorical_accuracy: 0.9645 - val_loss: 0.1508 - val_categorical_accuracy: 0.9538 - 859ms/epoch - 6ms/step
Epoch 149/250
141/141 - 1s - loss: 0.0849 - categorical_accuracy: 0.9712 - val_loss: 0.1352 - val_categorical_accuracy: 0.9578 - 860ms/epoch - 6ms/step
Epoch 150/250
141/141 - 1s - loss: 0.0797 - categorical_accuracy: 0.9727 - val_loss: 0.1651 - val_categorical_accuracy: 0.9516 - 860ms/epoch - 6ms/step
Epoch 151/250
141/141 - 1s - loss: 0.2019 - categorical_accuracy: 0.9416 - val_loss: 0.1581 - val_categorical_accuracy: 0.9495 - 876ms/epoch - 6ms/step
Epoch 152/250
141/141 - 1s - loss: 0.0812 - categorical_accuracy: 0.9723 - val_loss: 0.1581 - val_categorical_accuracy: 0.9531 - 892ms/epoch - 6ms/step
Epoch 153/250
141/141 - 1s - loss: 0.0865 - categorical_accuracy: 0.9704 - val_loss: 0.1703 - val_categorical_accuracy: 0.9449 - 844ms/epoch - 6ms/step
Epoch 154/250
141/141 - 1s - loss: 0.1144 - categorical_accuracy: 0.9634 - val_loss: 0.1467 - val_categorical_accuracy: 0.9547 - 872ms/epoch - 6ms/step
Epoch 155/250
141/141 - 1s - loss: 0.0807 - categorical_accuracy: 0.9727 - val_loss: 0.1529 - val_categorical_accuracy: 0.9556 - 861ms/epoch - 6ms/step
Epoch 156/250
141/141 - 1s - loss: 0.0892 - categorical_accuracy: 0.9698 - val_loss: 0.1754 - val_categorical_accuracy: 0.9460 - 875ms/epoch - 6ms/step
Epoch 157/250
141/141 - 1s - loss: 0.0864 - categorical_accuracy: 0.9705 - val_loss: 0.1596 - val_categorical_accuracy: 0.9510 - 873ms/epoch - 6ms/step
Epoch 158/250
141/141 - 1s - loss: 0.0804 - categorical_accuracy: 0.9724 - val_loss: 0.1501 - val_categorical_accuracy: 0.9559 - 879ms/epoch - 6ms/step
Epoch 159/250
141/141 - 1s - loss: 0.1002 - categorical_accuracy: 0.9671 - val_loss: 0.1451 - val_categorical_accuracy: 0.9535 - 856ms/epoch - 6ms/step
Epoch 160/250
141/141 - 1s - loss: 0.0825 - categorical_accuracy: 0.9720 - val_loss: 0.1953 - val_categorical_accuracy: 0.9409 - 856ms/epoch - 6ms/step
Epoch 161/250
141/141 - 1s - loss: 0.0791 - categorical_accuracy: 0.9727 - val_loss: 0.1712 - val_categorical_accuracy: 0.9501 - 872ms/epoch - 6ms/step
Epoch 162/250
141/141 - 1s - loss: 0.0913 - categorical_accuracy: 0.9691 - val_loss: 0.1474 - val_categorical_accuracy: 0.9546 - 861ms/epoch - 6ms/step
Epoch 163/250
141/141 - 1s - loss: 0.0780 - categorical_accuracy: 0.9732 - val_loss: 0.1645 - val_categorical_accuracy: 0.9500 - 846ms/epoch - 6ms/step
Epoch 164/250
141/141 - 1s - loss: 0.0999 - categorical_accuracy: 0.9662 - val_loss: 0.1345 - val_categorical_accuracy: 0.9589 - 872ms/epoch - 6ms/step
Epoch 165/250
141/141 - 1s - loss: 0.0864 - categorical_accuracy: 0.9708 - val_loss: 0.1547 - val_categorical_accuracy: 0.9531 - 893ms/epoch - 6ms/step
Epoch 166/250
141/141 - 1s - loss: 0.0803 - categorical_accuracy: 0.9726 - val_loss: 0.1668 - val_categorical_accuracy: 0.9511 - 859ms/epoch - 6ms/step
Epoch 167/250
141/141 - 1s - loss: 0.0798 - categorical_accuracy: 0.9723 - val_loss: 0.5231 - val_categorical_accuracy: 0.8710 - 871ms/epoch - 6ms/step
Epoch 168/250
141/141 - 1s - loss: 0.1050 - categorical_accuracy: 0.9672 - val_loss: 1.8323 - val_categorical_accuracy: 0.7291 - 860ms/epoch - 6ms/step
Epoch 169/250
141/141 - 1s - loss: 0.1166 - categorical_accuracy: 0.9646 - val_loss: 0.1386 - val_categorical_accuracy: 0.9582 - 860ms/epoch - 6ms/step
Epoch 170/250
141/141 - 1s - loss: 0.0760 - categorical_accuracy: 0.9740 - val_loss: 0.1374 - val_categorical_accuracy: 0.9582 - 846ms/epoch - 6ms/step
Epoch 171/250
141/141 - 1s - loss: 0.0740 - categorical_accuracy: 0.9746 - val_loss: 0.1513 - val_categorical_accuracy: 0.9522 - 844ms/epoch - 6ms/step
Epoch 172/250
141/141 - 1s - loss: 0.0830 - categorical_accuracy: 0.9716 - val_loss: 0.1456 - val_categorical_accuracy: 0.9550 - 879ms/epoch - 6ms/step
Epoch 173/250
141/141 - 1s - loss: 0.0834 - categorical_accuracy: 0.9718 - val_loss: 0.1474 - val_categorical_accuracy: 0.9555 - 863ms/epoch - 6ms/step
Epoch 174/250
141/141 - 1s - loss: 0.0773 - categorical_accuracy: 0.9734 - val_loss: 0.1488 - val_categorical_accuracy: 0.9564 - 872ms/epoch - 6ms/step
Epoch 175/250
141/141 - 1s - loss: 0.1213 - categorical_accuracy: 0.9634 - val_loss: 0.1474 - val_categorical_accuracy: 0.9549 - 844ms/epoch - 6ms/step
Epoch 176/250
141/141 - 1s - loss: 0.0744 - categorical_accuracy: 0.9747 - val_loss: 0.1555 - val_categorical_accuracy: 0.9561 - 859ms/epoch - 6ms/step
Epoch 177/250
141/141 - 1s - loss: 0.0744 - categorical_accuracy: 0.9744 - val_loss: 0.1687 - val_categorical_accuracy: 0.9517 - 859ms/epoch - 6ms/step
Epoch 178/250
141/141 - 1s - loss: 0.0925 - categorical_accuracy: 0.9702 - val_loss: 0.1506 - val_categorical_accuracy: 0.9538 - 861ms/epoch - 6ms/step
Epoch 179/250
141/141 - 1s - loss: 0.0991 - categorical_accuracy: 0.9685 - val_loss: 0.1490 - val_categorical_accuracy: 0.9551 - 845ms/epoch - 6ms/step
Epoch 180/250
141/141 - 1s - loss: 0.0775 - categorical_accuracy: 0.9739 - val_loss: 0.1486 - val_categorical_accuracy: 0.9551 - 873ms/epoch - 6ms/step
Epoch 181/250
141/141 - 1s - loss: 0.0777 - categorical_accuracy: 0.9734 - val_loss: 0.1639 - val_categorical_accuracy: 0.9531 - 859ms/epoch - 6ms/step
Epoch 182/250
141/141 - 1s - loss: 0.0740 - categorical_accuracy: 0.9744 - val_loss: 0.1544 - val_categorical_accuracy: 0.9532 - 909ms/epoch - 6ms/step
Epoch 183/250
141/141 - 1s - loss: 0.1010 - categorical_accuracy: 0.9676 - val_loss: 0.1557 - val_categorical_accuracy: 0.9504 - 893ms/epoch - 6ms/step
Epoch 184/250
141/141 - 1s - loss: 0.0728 - categorical_accuracy: 0.9753 - val_loss: 0.1386 - val_categorical_accuracy: 0.9597 - 890ms/epoch - 6ms/step
Epoch 185/250
141/141 - 1s - loss: 0.0713 - categorical_accuracy: 0.9754 - val_loss: 0.1578 - val_categorical_accuracy: 0.9532 - 890ms/epoch - 6ms/step
Epoch 186/250
141/141 - 1s - loss: 0.0912 - categorical_accuracy: 0.9701 - val_loss: 0.1703 - val_categorical_accuracy: 0.9498 - 908ms/epoch - 6ms/step
Epoch 187/250
141/141 - 1s - loss: 0.0707 - categorical_accuracy: 0.9757 - val_loss: 0.1551 - val_categorical_accuracy: 0.9555 - 921ms/epoch - 7ms/step
Epoch 188/250
141/141 - 1s - loss: 0.1039 - categorical_accuracy: 0.9679 - val_loss: 0.1446 - val_categorical_accuracy: 0.9570 - 902ms/epoch - 6ms/step
Epoch 189/250
141/141 - 1s - loss: 0.1023 - categorical_accuracy: 0.9678 - val_loss: 0.1386 - val_categorical_accuracy: 0.9578 - 906ms/epoch - 6ms/step
Epoch 190/250
141/141 - 1s - loss: 0.0679 - categorical_accuracy: 0.9769 - val_loss: 0.1416 - val_categorical_accuracy: 0.9580 - 905ms/epoch - 6ms/step
Epoch 191/250
141/141 - 1s - loss: 0.1929 - categorical_accuracy: 0.9474 - val_loss: 0.1606 - val_categorical_accuracy: 0.9500 - 895ms/epoch - 6ms/step
Epoch 192/250
141/141 - 1s - loss: 0.0761 - categorical_accuracy: 0.9742 - val_loss: 0.1470 - val_categorical_accuracy: 0.9563 - 939ms/epoch - 7ms/step
Epoch 193/250
141/141 - 1s - loss: 0.0715 - categorical_accuracy: 0.9758 - val_loss: 0.1605 - val_categorical_accuracy: 0.9503 - 891ms/epoch - 6ms/step
Epoch 194/250
141/141 - 1s - loss: 0.0716 - categorical_accuracy: 0.9753 - val_loss: 0.1418 - val_categorical_accuracy: 0.9589 - 892ms/epoch - 6ms/step
Epoch 195/250
141/141 - 1s - loss: 0.0918 - categorical_accuracy: 0.9704 - val_loss: 0.1663 - val_categorical_accuracy: 0.9502 - 891ms/epoch - 6ms/step
Epoch 196/250
141/141 - 1s - loss: 0.0696 - categorical_accuracy: 0.9764 - val_loss: 0.1390 - val_categorical_accuracy: 0.9600 - 891ms/epoch - 6ms/step
Epoch 197/250
141/141 - 1s - loss: 0.0684 - categorical_accuracy: 0.9764 - val_loss: 0.1663 - val_categorical_accuracy: 0.9482 - 884ms/epoch - 6ms/step
Epoch 198/250
141/141 - 1s - loss: 0.0702 - categorical_accuracy: 0.9759 - val_loss: 0.2038 - val_categorical_accuracy: 0.9429 - 872ms/epoch - 6ms/step
Epoch 199/250
141/141 - 1s - loss: 0.0792 - categorical_accuracy: 0.9733 - val_loss: 0.1526 - val_categorical_accuracy: 0.9539 - 873ms/epoch - 6ms/step
Epoch 200/250
141/141 - 1s - loss: 0.0687 - categorical_accuracy: 0.9766 - val_loss: 0.4272 - val_categorical_accuracy: 0.8804 - 860ms/epoch - 6ms/step
Epoch 201/250
141/141 - 1s - loss: 0.1627 - categorical_accuracy: 0.9537 - val_loss: 0.1440 - val_categorical_accuracy: 0.9559 - 938ms/epoch - 7ms/step
Epoch 202/250
141/141 - 1s - loss: 0.0665 - categorical_accuracy: 0.9775 - val_loss: 0.1412 - val_categorical_accuracy: 0.9583 - 857ms/epoch - 6ms/step
Epoch 203/250
141/141 - 1s - loss: 0.0683 - categorical_accuracy: 0.9766 - val_loss: 0.1560 - val_categorical_accuracy: 0.9549 - 876ms/epoch - 6ms/step
Epoch 204/250
141/141 - 1s - loss: 0.0700 - categorical_accuracy: 0.9759 - val_loss: 0.1516 - val_categorical_accuracy: 0.9569 - 924ms/epoch - 7ms/step
Epoch 205/250
141/141 - 1s - loss: 0.0706 - categorical_accuracy: 0.9757 - val_loss: 0.1565 - val_categorical_accuracy: 0.9532 - 908ms/epoch - 6ms/step
Epoch 206/250
141/141 - 1s - loss: 0.1514 - categorical_accuracy: 0.9566 - val_loss: 0.1412 - val_categorical_accuracy: 0.9586 - 874ms/epoch - 6ms/step
Epoch 207/250
141/141 - 1s - loss: 0.0660 - categorical_accuracy: 0.9777 - val_loss: 0.1484 - val_categorical_accuracy: 0.9581 - 893ms/epoch - 6ms/step
Epoch 208/250
141/141 - 1s - loss: 0.0788 - categorical_accuracy: 0.9744 - val_loss: 0.6052 - val_categorical_accuracy: 0.8378 - 908ms/epoch - 6ms/step
Epoch 209/250
141/141 - 1s - loss: 0.0847 - categorical_accuracy: 0.9724 - val_loss: 0.1563 - val_categorical_accuracy: 0.9555 - 907ms/epoch - 6ms/step
Epoch 210/250
141/141 - 1s - loss: 0.0670 - categorical_accuracy: 0.9771 - val_loss: 0.2885 - val_categorical_accuracy: 0.9104 - 923ms/epoch - 7ms/step
Epoch 211/250
141/141 - 1s - loss: 0.0842 - categorical_accuracy: 0.9722 - val_loss: 0.1463 - val_categorical_accuracy: 0.9566 - 927ms/epoch - 7ms/step
Epoch 212/250
141/141 - 1s - loss: 0.0649 - categorical_accuracy: 0.9777 - val_loss: 0.1547 - val_categorical_accuracy: 0.9567 - 921ms/epoch - 7ms/step
Epoch 213/250
141/141 - 1s - loss: 0.0662 - categorical_accuracy: 0.9775 - val_loss: 0.1618 - val_categorical_accuracy: 0.9543 - 901ms/epoch - 6ms/step
Epoch 214/250
141/141 - 1s - loss: 0.0683 - categorical_accuracy: 0.9763 - val_loss: 0.1480 - val_categorical_accuracy: 0.9568 - 884ms/epoch - 6ms/step
Epoch 215/250
141/141 - 1s - loss: 0.0698 - categorical_accuracy: 0.9761 - val_loss: 0.1834 - val_categorical_accuracy: 0.9466 - 917ms/epoch - 7ms/step
Epoch 216/250
141/141 - 1s - loss: 0.0935 - categorical_accuracy: 0.9706 - val_loss: 0.1613 - val_categorical_accuracy: 0.9489 - 919ms/epoch - 7ms/step
Epoch 217/250
141/141 - 1s - loss: 0.0664 - categorical_accuracy: 0.9774 - val_loss: 0.1452 - val_categorical_accuracy: 0.9584 - 918ms/epoch - 7ms/step
Epoch 218/250
141/141 - 1s - loss: 0.0634 - categorical_accuracy: 0.9781 - val_loss: 0.1997 - val_categorical_accuracy: 0.9460 - 908ms/epoch - 6ms/step
Epoch 219/250
141/141 - 1s - loss: 0.0976 - categorical_accuracy: 0.9696 - val_loss: 0.2669 - val_categorical_accuracy: 0.9282 - 923ms/epoch - 7ms/step
Epoch 220/250
141/141 - 1s - loss: 0.0865 - categorical_accuracy: 0.9721 - val_loss: 0.1545 - val_categorical_accuracy: 0.9566 - 923ms/epoch - 7ms/step
Epoch 221/250
141/141 - 1s - loss: 0.0657 - categorical_accuracy: 0.9775 - val_loss: 0.1742 - val_categorical_accuracy: 0.9535 - 914ms/epoch - 6ms/step
Epoch 222/250
141/141 - 1s - loss: 0.0932 - categorical_accuracy: 0.9706 - val_loss: 0.1380 - val_categorical_accuracy: 0.9610 - 890ms/epoch - 6ms/step
Epoch 223/250
141/141 - 1s - loss: 0.0626 - categorical_accuracy: 0.9787 - val_loss: 0.1517 - val_categorical_accuracy: 0.9586 - 901ms/epoch - 6ms/step
Epoch 224/250
141/141 - 1s - loss: 0.0616 - categorical_accuracy: 0.9785 - val_loss: 0.1604 - val_categorical_accuracy: 0.9527 - 899ms/epoch - 6ms/step
Epoch 225/250
141/141 - 1s - loss: 0.0683 - categorical_accuracy: 0.9764 - val_loss: 0.1641 - val_categorical_accuracy: 0.9528 - 925ms/epoch - 7ms/step
Epoch 226/250
141/141 - 1s - loss: 0.0635 - categorical_accuracy: 0.9778 - val_loss: 0.2001 - val_categorical_accuracy: 0.9435 - 910ms/epoch - 6ms/step
Epoch 227/250
141/141 - 1s - loss: 0.1692 - categorical_accuracy: 0.9519 - val_loss: 0.1421 - val_categorical_accuracy: 0.9599 - 895ms/epoch - 6ms/step
Epoch 228/250
141/141 - 1s - loss: 0.0625 - categorical_accuracy: 0.9785 - val_loss: 0.1469 - val_categorical_accuracy: 0.9592 - 906ms/epoch - 6ms/step
Epoch 229/250
141/141 - 1s - loss: 0.0614 - categorical_accuracy: 0.9789 - val_loss: 0.1566 - val_categorical_accuracy: 0.9557 - 911ms/epoch - 6ms/step
Epoch 230/250
141/141 - 1s - loss: 0.0897 - categorical_accuracy: 0.9709 - val_loss: 0.1570 - val_categorical_accuracy: 0.9530 - 909ms/epoch - 6ms/step
Epoch 231/250
141/141 - 1s - loss: 0.0643 - categorical_accuracy: 0.9780 - val_loss: 0.1544 - val_categorical_accuracy: 0.9565 - 904ms/epoch - 6ms/step
Epoch 232/250
141/141 - 1s - loss: 0.0621 - categorical_accuracy: 0.9785 - val_loss: 0.1655 - val_categorical_accuracy: 0.9554 - 907ms/epoch - 6ms/step
Epoch 233/250
141/141 - 1s - loss: 0.0613 - categorical_accuracy: 0.9790 - val_loss: 0.1724 - val_categorical_accuracy: 0.9531 - 910ms/epoch - 6ms/step
Epoch 234/250
141/141 - 1s - loss: 0.0652 - categorical_accuracy: 0.9774 - val_loss: 0.1462 - val_categorical_accuracy: 0.9602 - 949ms/epoch - 7ms/step
Epoch 235/250
141/141 - 1s - loss: 0.0636 - categorical_accuracy: 0.9781 - val_loss: 0.1933 - val_categorical_accuracy: 0.9468 - 921ms/epoch - 7ms/step
Epoch 236/250
141/141 - 1s - loss: 0.0620 - categorical_accuracy: 0.9784 - val_loss: 0.1665 - val_categorical_accuracy: 0.9533 - 910ms/epoch - 6ms/step
Epoch 237/250
141/141 - 1s - loss: 0.0650 - categorical_accuracy: 0.9775 - val_loss: 0.1641 - val_categorical_accuracy: 0.9520 - 893ms/epoch - 6ms/step
Epoch 238/250
141/141 - 1s - loss: 0.0669 - categorical_accuracy: 0.9764 - val_loss: 0.1802 - val_categorical_accuracy: 0.9503 - 904ms/epoch - 6ms/step
Epoch 239/250
141/141 - 1s - loss: 0.0612 - categorical_accuracy: 0.9789 - val_loss: 0.1547 - val_categorical_accuracy: 0.9576 - 941ms/epoch - 7ms/step
Epoch 240/250
141/141 - 1s - loss: 0.0613 - categorical_accuracy: 0.9788 - val_loss: 0.1758 - val_categorical_accuracy: 0.9516 - 904ms/epoch - 6ms/step
Epoch 241/250
141/141 - 1s - loss: 0.0622 - categorical_accuracy: 0.9782 - val_loss: 0.1600 - val_categorical_accuracy: 0.9560 - 888ms/epoch - 6ms/step
Epoch 242/250
141/141 - 1s - loss: 0.0965 - categorical_accuracy: 0.9708 - val_loss: 0.1553 - val_categorical_accuracy: 0.9562 - 922ms/epoch - 7ms/step
Epoch 243/250
141/141 - 1s - loss: 0.0612 - categorical_accuracy: 0.9790 - val_loss: 0.1617 - val_categorical_accuracy: 0.9549 - 906ms/epoch - 6ms/step
Epoch 244/250
141/141 - 1s - loss: 0.0638 - categorical_accuracy: 0.9780 - val_loss: 0.1811 - val_categorical_accuracy: 0.9519 - 911ms/epoch - 6ms/step
Epoch 245/250
141/141 - 1s - loss: 0.0644 - categorical_accuracy: 0.9779 - val_loss: 0.1545 - val_categorical_accuracy: 0.9582 - 905ms/epoch - 6ms/step
Epoch 246/250
141/141 - 1s - loss: 0.0591 - categorical_accuracy: 0.9794 - val_loss: 0.1513 - val_categorical_accuracy: 0.9572 - 920ms/epoch - 7ms/step
Epoch 247/250
141/141 - 1s - loss: 0.0768 - categorical_accuracy: 0.9746 - val_loss: 0.1463 - val_categorical_accuracy: 0.9592 - 895ms/epoch - 6ms/step
Epoch 248/250
141/141 - 1s - loss: 0.0835 - categorical_accuracy: 0.9728 - val_loss: 0.1563 - val_categorical_accuracy: 0.9527 - 906ms/epoch - 6ms/step
Epoch 249/250
141/141 - 1s - loss: 0.0611 - categorical_accuracy: 0.9792 - val_loss: 0.1525 - val_categorical_accuracy: 0.9591 - 925ms/epoch - 7ms/step
Epoch 250/250
141/141 - 1s - loss: 0.0610 - categorical_accuracy: 0.9788 - val_loss: 0.1773 - val_categorical_accuracy: 0.9517 - 907ms/epoch - 6ms/step
processing fold # 4 
Epoch 1/250
141/141 - 2s - loss: 1.9418 - categorical_accuracy: 0.2680 - val_loss: 1.8392 - val_categorical_accuracy: 0.2836 - 2s/epoch - 12ms/step
Epoch 2/250
141/141 - 1s - loss: 1.5267 - categorical_accuracy: 0.4201 - val_loss: 1.2919 - val_categorical_accuracy: 0.5199 - 972ms/epoch - 7ms/step
Epoch 3/250
141/141 - 1s - loss: 1.3042 - categorical_accuracy: 0.5021 - val_loss: 1.2687 - val_categorical_accuracy: 0.5245 - 941ms/epoch - 7ms/step
Epoch 4/250
141/141 - 1s - loss: 1.1848 - categorical_accuracy: 0.5536 - val_loss: 1.0759 - val_categorical_accuracy: 0.6066 - 940ms/epoch - 7ms/step
Epoch 5/250
141/141 - 1s - loss: 1.0304 - categorical_accuracy: 0.6103 - val_loss: 0.9708 - val_categorical_accuracy: 0.6261 - 940ms/epoch - 7ms/step
Epoch 6/250
141/141 - 1s - loss: 1.0510 - categorical_accuracy: 0.6112 - val_loss: 0.8280 - val_categorical_accuracy: 0.6994 - 942ms/epoch - 7ms/step
Epoch 7/250
141/141 - 1s - loss: 0.8479 - categorical_accuracy: 0.6782 - val_loss: 0.8667 - val_categorical_accuracy: 0.6808 - 959ms/epoch - 7ms/step
Epoch 8/250
141/141 - 1s - loss: 0.7956 - categorical_accuracy: 0.6998 - val_loss: 0.7036 - val_categorical_accuracy: 0.7328 - 942ms/epoch - 7ms/step
Epoch 9/250
141/141 - 1s - loss: 0.7619 - categorical_accuracy: 0.7164 - val_loss: 0.6618 - val_categorical_accuracy: 0.7542 - 910ms/epoch - 6ms/step
Epoch 10/250
141/141 - 1s - loss: 0.7134 - categorical_accuracy: 0.7344 - val_loss: 0.6972 - val_categorical_accuracy: 0.7354 - 921ms/epoch - 7ms/step
Epoch 11/250
141/141 - 1s - loss: 0.6497 - categorical_accuracy: 0.7556 - val_loss: 0.6254 - val_categorical_accuracy: 0.7591 - 911ms/epoch - 6ms/step
Epoch 12/250
141/141 - 1s - loss: 0.6378 - categorical_accuracy: 0.7618 - val_loss: 0.6077 - val_categorical_accuracy: 0.7661 - 926ms/epoch - 7ms/step
Epoch 13/250
141/141 - 1s - loss: 0.5804 - categorical_accuracy: 0.7806 - val_loss: 0.6568 - val_categorical_accuracy: 0.7527 - 908ms/epoch - 6ms/step
Epoch 14/250
141/141 - 1s - loss: 0.5716 - categorical_accuracy: 0.7881 - val_loss: 0.5117 - val_categorical_accuracy: 0.8083 - 942ms/epoch - 7ms/step
Epoch 15/250
141/141 - 1s - loss: 0.5721 - categorical_accuracy: 0.7900 - val_loss: 1.2358 - val_categorical_accuracy: 0.5850 - 937ms/epoch - 7ms/step
Epoch 16/250
141/141 - 1s - loss: 0.5143 - categorical_accuracy: 0.8087 - val_loss: 0.4900 - val_categorical_accuracy: 0.8205 - 921ms/epoch - 7ms/step
Epoch 17/250
141/141 - 1s - loss: 1.0301 - categorical_accuracy: 0.6597 - val_loss: 2.0688 - val_categorical_accuracy: 0.1357 - 941ms/epoch - 7ms/step
Epoch 18/250
141/141 - 1s - loss: 1.9554 - categorical_accuracy: 0.2384 - val_loss: 1.8276 - val_categorical_accuracy: 0.3111 - 937ms/epoch - 7ms/step
Epoch 19/250
141/141 - 1s - loss: 1.5256 - categorical_accuracy: 0.4357 - val_loss: 1.2291 - val_categorical_accuracy: 0.5530 - 927ms/epoch - 7ms/step
Epoch 20/250
141/141 - 1s - loss: 1.2261 - categorical_accuracy: 0.5536 - val_loss: 1.0474 - val_categorical_accuracy: 0.6247 - 909ms/epoch - 6ms/step
Epoch 21/250
141/141 - 1s - loss: 1.0178 - categorical_accuracy: 0.6242 - val_loss: 0.9498 - val_categorical_accuracy: 0.6452 - 941ms/epoch - 7ms/step
Epoch 22/250
141/141 - 1s - loss: 0.8762 - categorical_accuracy: 0.6728 - val_loss: 0.7737 - val_categorical_accuracy: 0.7158 - 941ms/epoch - 7ms/step
Epoch 23/250
141/141 - 1s - loss: 0.8514 - categorical_accuracy: 0.6922 - val_loss: 0.7711 - val_categorical_accuracy: 0.7096 - 923ms/epoch - 7ms/step
Epoch 24/250
141/141 - 1s - loss: 0.7407 - categorical_accuracy: 0.7280 - val_loss: 0.7182 - val_categorical_accuracy: 0.7356 - 889ms/epoch - 6ms/step
Epoch 25/250
141/141 - 1s - loss: 0.7435 - categorical_accuracy: 0.7341 - val_loss: 0.6316 - val_categorical_accuracy: 0.7635 - 926ms/epoch - 7ms/step
Epoch 26/250
141/141 - 1s - loss: 0.6244 - categorical_accuracy: 0.7697 - val_loss: 0.6504 - val_categorical_accuracy: 0.7646 - 923ms/epoch - 7ms/step
Epoch 27/250
141/141 - 1s - loss: 0.5976 - categorical_accuracy: 0.7807 - val_loss: 0.5898 - val_categorical_accuracy: 0.7893 - 925ms/epoch - 7ms/step
Epoch 28/250
141/141 - 1s - loss: 0.6330 - categorical_accuracy: 0.7741 - val_loss: 0.6004 - val_categorical_accuracy: 0.7942 - 908ms/epoch - 6ms/step
Epoch 29/250
141/141 - 1s - loss: 0.5355 - categorical_accuracy: 0.8049 - val_loss: 0.6824 - val_categorical_accuracy: 0.7614 - 941ms/epoch - 7ms/step
Epoch 30/250
141/141 - 1s - loss: 0.5302 - categorical_accuracy: 0.8078 - val_loss: 0.5047 - val_categorical_accuracy: 0.8225 - 925ms/epoch - 7ms/step
Epoch 31/250
141/141 - 1s - loss: 0.5003 - categorical_accuracy: 0.8187 - val_loss: 0.4963 - val_categorical_accuracy: 0.8201 - 918ms/epoch - 7ms/step
Epoch 32/250
141/141 - 1s - loss: 0.4920 - categorical_accuracy: 0.8232 - val_loss: 0.5028 - val_categorical_accuracy: 0.8171 - 939ms/epoch - 7ms/step
Epoch 33/250
141/141 - 1s - loss: 0.5560 - categorical_accuracy: 0.8089 - val_loss: 0.4372 - val_categorical_accuracy: 0.8465 - 923ms/epoch - 7ms/step
Epoch 34/250
141/141 - 1s - loss: 0.4525 - categorical_accuracy: 0.8380 - val_loss: 0.4595 - val_categorical_accuracy: 0.8266 - 919ms/epoch - 7ms/step
Epoch 35/250
141/141 - 1s - loss: 0.4404 - categorical_accuracy: 0.8405 - val_loss: 0.4794 - val_categorical_accuracy: 0.8246 - 905ms/epoch - 6ms/step
Epoch 36/250
141/141 - 1s - loss: 0.4300 - categorical_accuracy: 0.8459 - val_loss: 0.4476 - val_categorical_accuracy: 0.8371 - 924ms/epoch - 7ms/step
Epoch 37/250
141/141 - 1s - loss: 0.5243 - categorical_accuracy: 0.8241 - val_loss: 0.4123 - val_categorical_accuracy: 0.8585 - 954ms/epoch - 7ms/step
Epoch 38/250
141/141 - 1s - loss: 0.3968 - categorical_accuracy: 0.8576 - val_loss: 0.3862 - val_categorical_accuracy: 0.8637 - 939ms/epoch - 7ms/step
Epoch 39/250
141/141 - 1s - loss: 0.3924 - categorical_accuracy: 0.8594 - val_loss: 0.3947 - val_categorical_accuracy: 0.8593 - 936ms/epoch - 7ms/step
Epoch 40/250
141/141 - 1s - loss: 0.3989 - categorical_accuracy: 0.8583 - val_loss: 0.3705 - val_categorical_accuracy: 0.8706 - 927ms/epoch - 7ms/step
Epoch 41/250
141/141 - 1s - loss: 0.3621 - categorical_accuracy: 0.8701 - val_loss: 0.4640 - val_categorical_accuracy: 0.8382 - 909ms/epoch - 6ms/step
Epoch 42/250
141/141 - 1s - loss: 0.4368 - categorical_accuracy: 0.8531 - val_loss: 1.2546 - val_categorical_accuracy: 0.5677 - 933ms/epoch - 7ms/step
Epoch 43/250
141/141 - 1s - loss: 0.4427 - categorical_accuracy: 0.8460 - val_loss: 0.3916 - val_categorical_accuracy: 0.8647 - 1s/epoch - 8ms/step
Epoch 44/250
141/141 - 1s - loss: 0.3536 - categorical_accuracy: 0.8740 - val_loss: 0.4322 - val_categorical_accuracy: 0.8406 - 925ms/epoch - 7ms/step
Epoch 45/250
141/141 - 1s - loss: 0.3585 - categorical_accuracy: 0.8735 - val_loss: 0.3596 - val_categorical_accuracy: 0.8747 - 925ms/epoch - 7ms/step
Epoch 46/250
141/141 - 1s - loss: 0.3299 - categorical_accuracy: 0.8824 - val_loss: 0.3503 - val_categorical_accuracy: 0.8754 - 922ms/epoch - 7ms/step
Epoch 47/250
141/141 - 1s - loss: 0.3586 - categorical_accuracy: 0.8769 - val_loss: 0.3546 - val_categorical_accuracy: 0.8736 - 922ms/epoch - 7ms/step
Epoch 48/250
141/141 - 1s - loss: 0.3142 - categorical_accuracy: 0.8883 - val_loss: 0.3127 - val_categorical_accuracy: 0.8920 - 937ms/epoch - 7ms/step
Epoch 49/250
141/141 - 1s - loss: 0.3088 - categorical_accuracy: 0.8899 - val_loss: 0.3781 - val_categorical_accuracy: 0.8632 - 957ms/epoch - 7ms/step
Epoch 50/250
141/141 - 1s - loss: 0.3351 - categorical_accuracy: 0.8839 - val_loss: 0.3215 - val_categorical_accuracy: 0.8854 - 935ms/epoch - 7ms/step
Epoch 51/250
141/141 - 1s - loss: 0.3022 - categorical_accuracy: 0.8935 - val_loss: 0.3228 - val_categorical_accuracy: 0.8866 - 942ms/epoch - 7ms/step
Epoch 52/250
141/141 - 1s - loss: 0.2970 - categorical_accuracy: 0.8940 - val_loss: 0.3096 - val_categorical_accuracy: 0.8909 - 942ms/epoch - 7ms/step
Epoch 53/250
141/141 - 1s - loss: 0.2894 - categorical_accuracy: 0.8978 - val_loss: 0.4063 - val_categorical_accuracy: 0.8484 - 939ms/epoch - 7ms/step
Epoch 54/250
141/141 - 1s - loss: 0.3247 - categorical_accuracy: 0.8899 - val_loss: 0.3646 - val_categorical_accuracy: 0.8732 - 909ms/epoch - 6ms/step
Epoch 55/250
141/141 - 1s - loss: 0.2752 - categorical_accuracy: 0.9035 - val_loss: 0.3081 - val_categorical_accuracy: 0.8894 - 925ms/epoch - 7ms/step
Epoch 56/250
141/141 - 1s - loss: 0.2734 - categorical_accuracy: 0.9032 - val_loss: 0.2718 - val_categorical_accuracy: 0.9063 - 924ms/epoch - 7ms/step
Epoch 57/250
141/141 - 1s - loss: 0.2970 - categorical_accuracy: 0.8985 - val_loss: 0.2730 - val_categorical_accuracy: 0.9055 - 923ms/epoch - 7ms/step
Epoch 58/250
141/141 - 1s - loss: 0.2815 - categorical_accuracy: 0.9016 - val_loss: 0.2979 - val_categorical_accuracy: 0.8977 - 922ms/epoch - 7ms/step
Epoch 59/250
141/141 - 1s - loss: 0.2561 - categorical_accuracy: 0.9096 - val_loss: 0.3003 - val_categorical_accuracy: 0.8963 - 939ms/epoch - 7ms/step
Epoch 60/250
141/141 - 1s - loss: 0.3511 - categorical_accuracy: 0.8864 - val_loss: 0.2779 - val_categorical_accuracy: 0.9044 - 942ms/epoch - 7ms/step
Epoch 61/250
141/141 - 1s - loss: 0.2504 - categorical_accuracy: 0.9121 - val_loss: 0.2639 - val_categorical_accuracy: 0.9073 - 922ms/epoch - 7ms/step
Epoch 62/250
141/141 - 1s - loss: 0.2425 - categorical_accuracy: 0.9148 - val_loss: 0.3074 - val_categorical_accuracy: 0.8945 - 940ms/epoch - 7ms/step
Epoch 63/250
141/141 - 1s - loss: 0.2451 - categorical_accuracy: 0.9147 - val_loss: 0.2588 - val_categorical_accuracy: 0.9082 - 924ms/epoch - 7ms/step
Epoch 64/250
141/141 - 1s - loss: 0.3059 - categorical_accuracy: 0.8976 - val_loss: 0.2713 - val_categorical_accuracy: 0.9066 - 938ms/epoch - 7ms/step
Epoch 65/250
141/141 - 1s - loss: 0.2265 - categorical_accuracy: 0.9215 - val_loss: 0.2794 - val_categorical_accuracy: 0.9040 - 927ms/epoch - 7ms/step
Epoch 66/250
141/141 - 1s - loss: 0.2326 - categorical_accuracy: 0.9187 - val_loss: 0.2731 - val_categorical_accuracy: 0.9021 - 940ms/epoch - 7ms/step
Epoch 67/250
141/141 - 1s - loss: 0.2326 - categorical_accuracy: 0.9184 - val_loss: 0.3136 - val_categorical_accuracy: 0.8868 - 924ms/epoch - 7ms/step
Epoch 68/250
141/141 - 1s - loss: 0.2917 - categorical_accuracy: 0.9045 - val_loss: 0.2669 - val_categorical_accuracy: 0.9058 - 923ms/epoch - 7ms/step
Epoch 69/250
141/141 - 1s - loss: 0.2243 - categorical_accuracy: 0.9214 - val_loss: 0.3117 - val_categorical_accuracy: 0.8948 - 942ms/epoch - 7ms/step
Epoch 70/250
141/141 - 1s - loss: 0.2191 - categorical_accuracy: 0.9233 - val_loss: 0.2420 - val_categorical_accuracy: 0.9175 - 958ms/epoch - 7ms/step
Epoch 71/250
141/141 - 1s - loss: 0.2401 - categorical_accuracy: 0.9164 - val_loss: 0.2551 - val_categorical_accuracy: 0.9128 - 925ms/epoch - 7ms/step
Epoch 72/250
141/141 - 1s - loss: 0.2089 - categorical_accuracy: 0.9271 - val_loss: 0.2374 - val_categorical_accuracy: 0.9191 - 924ms/epoch - 7ms/step
Epoch 73/250
141/141 - 1s - loss: 0.2137 - categorical_accuracy: 0.9252 - val_loss: 0.2541 - val_categorical_accuracy: 0.9130 - 901ms/epoch - 6ms/step
Epoch 74/250
141/141 - 1s - loss: 0.2071 - categorical_accuracy: 0.9277 - val_loss: 0.2791 - val_categorical_accuracy: 0.9039 - 915ms/epoch - 6ms/step
Epoch 75/250
141/141 - 1s - loss: 0.3395 - categorical_accuracy: 0.8953 - val_loss: 0.2286 - val_categorical_accuracy: 0.9226 - 915ms/epoch - 6ms/step
Epoch 76/250
141/141 - 1s - loss: 0.2035 - categorical_accuracy: 0.9296 - val_loss: 0.2577 - val_categorical_accuracy: 0.9098 - 942ms/epoch - 7ms/step
Epoch 77/250
141/141 - 1s - loss: 0.2013 - categorical_accuracy: 0.9301 - val_loss: 0.3449 - val_categorical_accuracy: 0.8848 - 907ms/epoch - 6ms/step
Epoch 78/250
141/141 - 1s - loss: 0.2390 - categorical_accuracy: 0.9217 - val_loss: 0.2312 - val_categorical_accuracy: 0.9204 - 891ms/epoch - 6ms/step
Epoch 79/250
141/141 - 1s - loss: 0.2013 - categorical_accuracy: 0.9300 - val_loss: 0.3249 - val_categorical_accuracy: 0.8863 - 891ms/epoch - 6ms/step
Epoch 80/250
141/141 - 1s - loss: 0.1992 - categorical_accuracy: 0.9305 - val_loss: 0.2561 - val_categorical_accuracy: 0.9121 - 876ms/epoch - 6ms/step
Epoch 81/250
141/141 - 1s - loss: 0.2055 - categorical_accuracy: 0.9301 - val_loss: 0.2144 - val_categorical_accuracy: 0.9263 - 894ms/epoch - 6ms/step
Epoch 82/250
141/141 - 1s - loss: 0.1933 - categorical_accuracy: 0.9333 - val_loss: 0.2264 - val_categorical_accuracy: 0.9221 - 863ms/epoch - 6ms/step
Epoch 83/250
141/141 - 1s - loss: 0.2090 - categorical_accuracy: 0.9288 - val_loss: 0.6931 - val_categorical_accuracy: 0.7963 - 890ms/epoch - 6ms/step
Epoch 84/250
141/141 - 1s - loss: 0.1972 - categorical_accuracy: 0.9317 - val_loss: 0.2205 - val_categorical_accuracy: 0.9240 - 878ms/epoch - 6ms/step
Epoch 85/250
141/141 - 1s - loss: 0.1779 - categorical_accuracy: 0.9386 - val_loss: 0.2211 - val_categorical_accuracy: 0.9240 - 878ms/epoch - 6ms/step
Epoch 86/250
141/141 - 1s - loss: 0.1813 - categorical_accuracy: 0.9370 - val_loss: 0.2352 - val_categorical_accuracy: 0.9192 - 877ms/epoch - 6ms/step
Epoch 87/250
141/141 - 1s - loss: 0.1839 - categorical_accuracy: 0.9366 - val_loss: 0.2279 - val_categorical_accuracy: 0.9226 - 877ms/epoch - 6ms/step
Epoch 88/250
141/141 - 1s - loss: 0.1887 - categorical_accuracy: 0.9345 - val_loss: 0.2111 - val_categorical_accuracy: 0.9281 - 873ms/epoch - 6ms/step
Epoch 89/250
141/141 - 1s - loss: 0.2243 - categorical_accuracy: 0.9282 - val_loss: 0.2827 - val_categorical_accuracy: 0.9071 - 877ms/epoch - 6ms/step
Epoch 90/250
141/141 - 1s - loss: 0.1739 - categorical_accuracy: 0.9400 - val_loss: 0.2270 - val_categorical_accuracy: 0.9232 - 878ms/epoch - 6ms/step
Epoch 91/250
141/141 - 1s - loss: 0.1759 - categorical_accuracy: 0.9392 - val_loss: 0.2291 - val_categorical_accuracy: 0.9209 - 861ms/epoch - 6ms/step
Epoch 92/250
141/141 - 1s - loss: 0.1722 - categorical_accuracy: 0.9402 - val_loss: 0.2124 - val_categorical_accuracy: 0.9273 - 858ms/epoch - 6ms/step
Epoch 93/250
141/141 - 1s - loss: 0.3809 - categorical_accuracy: 0.8900 - val_loss: 0.3490 - val_categorical_accuracy: 0.8808 - 875ms/epoch - 6ms/step
Epoch 94/250
141/141 - 1s - loss: 0.1921 - categorical_accuracy: 0.9346 - val_loss: 0.2269 - val_categorical_accuracy: 0.9215 - 892ms/epoch - 6ms/step
Epoch 95/250
141/141 - 1s - loss: 0.1705 - categorical_accuracy: 0.9417 - val_loss: 0.2314 - val_categorical_accuracy: 0.9201 - 872ms/epoch - 6ms/step
Epoch 96/250
141/141 - 1s - loss: 0.1691 - categorical_accuracy: 0.9413 - val_loss: 0.2763 - val_categorical_accuracy: 0.9083 - 862ms/epoch - 6ms/step
Epoch 97/250
141/141 - 1s - loss: 0.1686 - categorical_accuracy: 0.9419 - val_loss: 0.2087 - val_categorical_accuracy: 0.9299 - 892ms/epoch - 6ms/step
Epoch 98/250
141/141 - 1s - loss: 0.1693 - categorical_accuracy: 0.9412 - val_loss: 0.2037 - val_categorical_accuracy: 0.9305 - 890ms/epoch - 6ms/step
Epoch 99/250
141/141 - 1s - loss: 0.1619 - categorical_accuracy: 0.9438 - val_loss: 0.2753 - val_categorical_accuracy: 0.9042 - 859ms/epoch - 6ms/step
Epoch 100/250
141/141 - 1s - loss: 0.2025 - categorical_accuracy: 0.9342 - val_loss: 0.2529 - val_categorical_accuracy: 0.9135 - 845ms/epoch - 6ms/step
Epoch 101/250
141/141 - 1s - loss: 0.1632 - categorical_accuracy: 0.9443 - val_loss: 0.2215 - val_categorical_accuracy: 0.9244 - 877ms/epoch - 6ms/step
Epoch 102/250
141/141 - 1s - loss: 0.1686 - categorical_accuracy: 0.9429 - val_loss: 0.2034 - val_categorical_accuracy: 0.9316 - 859ms/epoch - 6ms/step
Epoch 103/250
141/141 - 1s - loss: 0.1582 - categorical_accuracy: 0.9460 - val_loss: 0.2100 - val_categorical_accuracy: 0.9299 - 871ms/epoch - 6ms/step
Epoch 104/250
141/141 - 1s - loss: 0.3967 - categorical_accuracy: 0.8895 - val_loss: 0.2107 - val_categorical_accuracy: 0.9290 - 869ms/epoch - 6ms/step
Epoch 105/250
141/141 - 1s - loss: 0.1585 - categorical_accuracy: 0.9457 - val_loss: 0.2044 - val_categorical_accuracy: 0.9316 - 872ms/epoch - 6ms/step
Epoch 106/250
141/141 - 1s - loss: 0.1534 - categorical_accuracy: 0.9472 - val_loss: 0.2306 - val_categorical_accuracy: 0.9216 - 878ms/epoch - 6ms/step
Epoch 107/250
141/141 - 1s - loss: 0.1569 - categorical_accuracy: 0.9459 - val_loss: 0.3320 - val_categorical_accuracy: 0.8936 - 863ms/epoch - 6ms/step
Epoch 108/250
141/141 - 1s - loss: 0.1521 - categorical_accuracy: 0.9479 - val_loss: 0.1994 - val_categorical_accuracy: 0.9333 - 874ms/epoch - 6ms/step
Epoch 109/250
141/141 - 1s - loss: 0.1569 - categorical_accuracy: 0.9458 - val_loss: 0.1925 - val_categorical_accuracy: 0.9357 - 877ms/epoch - 6ms/step
Epoch 110/250
141/141 - 1s - loss: 0.1469 - categorical_accuracy: 0.9496 - val_loss: 0.2179 - val_categorical_accuracy: 0.9279 - 891ms/epoch - 6ms/step
Epoch 111/250
141/141 - 1s - loss: 0.1914 - categorical_accuracy: 0.9381 - val_loss: 0.2105 - val_categorical_accuracy: 0.9286 - 871ms/epoch - 6ms/step
Epoch 112/250
141/141 - 1s - loss: 0.1407 - categorical_accuracy: 0.9519 - val_loss: 0.2322 - val_categorical_accuracy: 0.9219 - 874ms/epoch - 6ms/step
Epoch 113/250
141/141 - 1s - loss: 0.1439 - categorical_accuracy: 0.9508 - val_loss: 0.2019 - val_categorical_accuracy: 0.9333 - 878ms/epoch - 6ms/step
Epoch 114/250
141/141 - 1s - loss: 0.1682 - categorical_accuracy: 0.9438 - val_loss: 0.1861 - val_categorical_accuracy: 0.9382 - 877ms/epoch - 6ms/step
Epoch 115/250
141/141 - 1s - loss: 0.1440 - categorical_accuracy: 0.9504 - val_loss: 0.1918 - val_categorical_accuracy: 0.9353 - 873ms/epoch - 6ms/step
Epoch 116/250
141/141 - 1s - loss: 0.2139 - categorical_accuracy: 0.9349 - val_loss: 0.1910 - val_categorical_accuracy: 0.9341 - 862ms/epoch - 6ms/step
Epoch 117/250
141/141 - 1s - loss: 0.1369 - categorical_accuracy: 0.9532 - val_loss: 0.2017 - val_categorical_accuracy: 0.9309 - 878ms/epoch - 6ms/step
Epoch 118/250
141/141 - 1s - loss: 0.1457 - categorical_accuracy: 0.9501 - val_loss: 0.2616 - val_categorical_accuracy: 0.9118 - 860ms/epoch - 6ms/step
Epoch 119/250
141/141 - 1s - loss: 0.1375 - categorical_accuracy: 0.9531 - val_loss: 0.2132 - val_categorical_accuracy: 0.9284 - 890ms/epoch - 6ms/step
Epoch 120/250
141/141 - 1s - loss: 0.1814 - categorical_accuracy: 0.9420 - val_loss: 0.1864 - val_categorical_accuracy: 0.9387 - 860ms/epoch - 6ms/step
Epoch 121/250
141/141 - 1s - loss: 0.1351 - categorical_accuracy: 0.9536 - val_loss: 0.2220 - val_categorical_accuracy: 0.9269 - 860ms/epoch - 6ms/step
Epoch 122/250
141/141 - 1s - loss: 0.1456 - categorical_accuracy: 0.9506 - val_loss: 0.2162 - val_categorical_accuracy: 0.9271 - 845ms/epoch - 6ms/step
Epoch 123/250
141/141 - 1s - loss: 0.1369 - categorical_accuracy: 0.9529 - val_loss: 0.2009 - val_categorical_accuracy: 0.9352 - 877ms/epoch - 6ms/step
Epoch 124/250
141/141 - 1s - loss: 0.1747 - categorical_accuracy: 0.9433 - val_loss: 0.1922 - val_categorical_accuracy: 0.9372 - 874ms/epoch - 6ms/step
Epoch 125/250
141/141 - 1s - loss: 0.1450 - categorical_accuracy: 0.9523 - val_loss: 0.1864 - val_categorical_accuracy: 0.9383 - 861ms/epoch - 6ms/step
Epoch 126/250
141/141 - 1s - loss: 0.1371 - categorical_accuracy: 0.9529 - val_loss: 0.1944 - val_categorical_accuracy: 0.9340 - 873ms/epoch - 6ms/step
Epoch 127/250
141/141 - 1s - loss: 0.1438 - categorical_accuracy: 0.9519 - val_loss: 0.2332 - val_categorical_accuracy: 0.9215 - 883ms/epoch - 6ms/step
Epoch 128/250
141/141 - 1s - loss: 0.1266 - categorical_accuracy: 0.9567 - val_loss: 0.3056 - val_categorical_accuracy: 0.9002 - 875ms/epoch - 6ms/step
Epoch 129/250
141/141 - 1s - loss: 0.1494 - categorical_accuracy: 0.9506 - val_loss: 0.1827 - val_categorical_accuracy: 0.9408 - 862ms/epoch - 6ms/step
Epoch 130/250
141/141 - 1s - loss: 0.1380 - categorical_accuracy: 0.9523 - val_loss: 0.2612 - val_categorical_accuracy: 0.9122 - 891ms/epoch - 6ms/step
Epoch 131/250
141/141 - 1s - loss: 0.1267 - categorical_accuracy: 0.9569 - val_loss: 0.2442 - val_categorical_accuracy: 0.9180 - 876ms/epoch - 6ms/step
Epoch 132/250
141/141 - 1s - loss: 0.1431 - categorical_accuracy: 0.9513 - val_loss: 0.1936 - val_categorical_accuracy: 0.9363 - 860ms/epoch - 6ms/step
Epoch 133/250
141/141 - 1s - loss: 0.2345 - categorical_accuracy: 0.9325 - val_loss: 0.2103 - val_categorical_accuracy: 0.9293 - 872ms/epoch - 6ms/step
Epoch 134/250
141/141 - 1s - loss: 0.1247 - categorical_accuracy: 0.9580 - val_loss: 0.1840 - val_categorical_accuracy: 0.9401 - 861ms/epoch - 6ms/step
Epoch 135/250
141/141 - 1s - loss: 0.1196 - categorical_accuracy: 0.9592 - val_loss: 0.1892 - val_categorical_accuracy: 0.9386 - 861ms/epoch - 6ms/step
Epoch 136/250
141/141 - 1s - loss: 0.1669 - categorical_accuracy: 0.9486 - val_loss: 0.1943 - val_categorical_accuracy: 0.9385 - 859ms/epoch - 6ms/step
Epoch 137/250
141/141 - 1s - loss: 0.1360 - categorical_accuracy: 0.9538 - val_loss: 0.1868 - val_categorical_accuracy: 0.9394 - 892ms/epoch - 6ms/step
Epoch 138/250
141/141 - 1s - loss: 0.1196 - categorical_accuracy: 0.9589 - val_loss: 0.2000 - val_categorical_accuracy: 0.9342 - 894ms/epoch - 6ms/step
Epoch 139/250
141/141 - 1s - loss: 0.1284 - categorical_accuracy: 0.9562 - val_loss: 0.1890 - val_categorical_accuracy: 0.9379 - 895ms/epoch - 6ms/step
Epoch 140/250
141/141 - 1s - loss: 0.1264 - categorical_accuracy: 0.9567 - val_loss: 0.2090 - val_categorical_accuracy: 0.9348 - 860ms/epoch - 6ms/step
Epoch 141/250
141/141 - 1s - loss: 0.1228 - categorical_accuracy: 0.9577 - val_loss: 0.1910 - val_categorical_accuracy: 0.9390 - 877ms/epoch - 6ms/step
Epoch 142/250
141/141 - 1s - loss: 0.1246 - categorical_accuracy: 0.9576 - val_loss: 0.1862 - val_categorical_accuracy: 0.9402 - 876ms/epoch - 6ms/step
Epoch 143/250
141/141 - 1s - loss: 0.1120 - categorical_accuracy: 0.9617 - val_loss: 0.1975 - val_categorical_accuracy: 0.9347 - 892ms/epoch - 6ms/step
Epoch 144/250
141/141 - 1s - loss: 0.1678 - categorical_accuracy: 0.9479 - val_loss: 0.1828 - val_categorical_accuracy: 0.9397 - 873ms/epoch - 6ms/step
Epoch 145/250
141/141 - 1s - loss: 0.1128 - categorical_accuracy: 0.9619 - val_loss: 0.1847 - val_categorical_accuracy: 0.9395 - 888ms/epoch - 6ms/step
Epoch 146/250
141/141 - 1s - loss: 0.1248 - categorical_accuracy: 0.9571 - val_loss: 0.2033 - val_categorical_accuracy: 0.9352 - 861ms/epoch - 6ms/step
Epoch 147/250
141/141 - 1s - loss: 0.1263 - categorical_accuracy: 0.9568 - val_loss: 0.1835 - val_categorical_accuracy: 0.9404 - 854ms/epoch - 6ms/step
Epoch 148/250
141/141 - 1s - loss: 0.1128 - categorical_accuracy: 0.9612 - val_loss: 0.1902 - val_categorical_accuracy: 0.9392 - 875ms/epoch - 6ms/step
Epoch 149/250
141/141 - 1s - loss: 0.1176 - categorical_accuracy: 0.9599 - val_loss: 0.2072 - val_categorical_accuracy: 0.9292 - 882ms/epoch - 6ms/step
Epoch 150/250
141/141 - 1s - loss: 0.1159 - categorical_accuracy: 0.9598 - val_loss: 0.2577 - val_categorical_accuracy: 0.9191 - 872ms/epoch - 6ms/step
Epoch 151/250
141/141 - 1s - loss: 0.1198 - categorical_accuracy: 0.9591 - val_loss: 0.1976 - val_categorical_accuracy: 0.9378 - 871ms/epoch - 6ms/step
Epoch 152/250
141/141 - 1s - loss: 0.1805 - categorical_accuracy: 0.9451 - val_loss: 0.1804 - val_categorical_accuracy: 0.9419 - 858ms/epoch - 6ms/step
Epoch 153/250
141/141 - 1s - loss: 0.1064 - categorical_accuracy: 0.9637 - val_loss: 0.2030 - val_categorical_accuracy: 0.9340 - 870ms/epoch - 6ms/step
Epoch 154/250
141/141 - 1s - loss: 0.1651 - categorical_accuracy: 0.9490 - val_loss: 0.1837 - val_categorical_accuracy: 0.9399 - 875ms/epoch - 6ms/step
Epoch 155/250
141/141 - 1s - loss: 0.1077 - categorical_accuracy: 0.9633 - val_loss: 0.1812 - val_categorical_accuracy: 0.9410 - 875ms/epoch - 6ms/step
Epoch 156/250
141/141 - 1s - loss: 0.1087 - categorical_accuracy: 0.9624 - val_loss: 0.4092 - val_categorical_accuracy: 0.8744 - 861ms/epoch - 6ms/step
Epoch 157/250
141/141 - 1s - loss: 0.1263 - categorical_accuracy: 0.9583 - val_loss: 0.1725 - val_categorical_accuracy: 0.9454 - 876ms/epoch - 6ms/step
Epoch 158/250
141/141 - 1s - loss: 0.1501 - categorical_accuracy: 0.9541 - val_loss: 0.1805 - val_categorical_accuracy: 0.9425 - 875ms/epoch - 6ms/step
Epoch 159/250
141/141 - 1s - loss: 0.1066 - categorical_accuracy: 0.9636 - val_loss: 0.2087 - val_categorical_accuracy: 0.9335 - 876ms/epoch - 6ms/step
Epoch 160/250
141/141 - 1s - loss: 0.1271 - categorical_accuracy: 0.9584 - val_loss: 0.1848 - val_categorical_accuracy: 0.9390 - 858ms/epoch - 6ms/step
Epoch 161/250
141/141 - 1s - loss: 0.1062 - categorical_accuracy: 0.9634 - val_loss: 0.1784 - val_categorical_accuracy: 0.9420 - 871ms/epoch - 6ms/step
Epoch 162/250
141/141 - 1s - loss: 0.1155 - categorical_accuracy: 0.9607 - val_loss: 0.2052 - val_categorical_accuracy: 0.9323 - 857ms/epoch - 6ms/step
Epoch 163/250
141/141 - 1s - loss: 0.1176 - categorical_accuracy: 0.9608 - val_loss: 0.1864 - val_categorical_accuracy: 0.9410 - 871ms/epoch - 6ms/step
Epoch 164/250
141/141 - 1s - loss: 0.1082 - categorical_accuracy: 0.9629 - val_loss: 0.1954 - val_categorical_accuracy: 0.9383 - 873ms/epoch - 6ms/step
Epoch 165/250
141/141 - 1s - loss: 0.1051 - categorical_accuracy: 0.9642 - val_loss: 0.1899 - val_categorical_accuracy: 0.9413 - 886ms/epoch - 6ms/step
Epoch 166/250
141/141 - 1s - loss: 0.1368 - categorical_accuracy: 0.9557 - val_loss: 0.1796 - val_categorical_accuracy: 0.9437 - 892ms/epoch - 6ms/step
Epoch 167/250
141/141 - 1s - loss: 0.1069 - categorical_accuracy: 0.9633 - val_loss: 0.1848 - val_categorical_accuracy: 0.9415 - 863ms/epoch - 6ms/step
Epoch 168/250
141/141 - 1s - loss: 0.1012 - categorical_accuracy: 0.9655 - val_loss: 0.1875 - val_categorical_accuracy: 0.9390 - 860ms/epoch - 6ms/step
Epoch 169/250
141/141 - 1s - loss: 0.1040 - categorical_accuracy: 0.9646 - val_loss: 0.2090 - val_categorical_accuracy: 0.9372 - 862ms/epoch - 6ms/step
Epoch 170/250
141/141 - 1s - loss: 0.1131 - categorical_accuracy: 0.9614 - val_loss: 0.2528 - val_categorical_accuracy: 0.9221 - 873ms/epoch - 6ms/step
Epoch 171/250
141/141 - 1s - loss: 0.1122 - categorical_accuracy: 0.9619 - val_loss: 0.1729 - val_categorical_accuracy: 0.9447 - 860ms/epoch - 6ms/step
Epoch 172/250
141/141 - 1s - loss: 0.1045 - categorical_accuracy: 0.9645 - val_loss: 0.1945 - val_categorical_accuracy: 0.9401 - 888ms/epoch - 6ms/step
Epoch 173/250
141/141 - 1s - loss: 0.0978 - categorical_accuracy: 0.9667 - val_loss: 0.2092 - val_categorical_accuracy: 0.9348 - 885ms/epoch - 6ms/step
Epoch 174/250
141/141 - 1s - loss: 0.1042 - categorical_accuracy: 0.9643 - val_loss: 0.1973 - val_categorical_accuracy: 0.9388 - 872ms/epoch - 6ms/step
Epoch 175/250
141/141 - 1s - loss: 0.1435 - categorical_accuracy: 0.9568 - val_loss: 0.1615 - val_categorical_accuracy: 0.9495 - 870ms/epoch - 6ms/step
Epoch 176/250
141/141 - 1s - loss: 0.0970 - categorical_accuracy: 0.9670 - val_loss: 0.1951 - val_categorical_accuracy: 0.9359 - 873ms/epoch - 6ms/step
Epoch 177/250
141/141 - 1s - loss: 0.1939 - categorical_accuracy: 0.9444 - val_loss: 0.1752 - val_categorical_accuracy: 0.9439 - 886ms/epoch - 6ms/step
Epoch 178/250
141/141 - 1s - loss: 0.0946 - categorical_accuracy: 0.9680 - val_loss: 0.1668 - val_categorical_accuracy: 0.9482 - 871ms/epoch - 6ms/step
Epoch 179/250
141/141 - 1s - loss: 0.0958 - categorical_accuracy: 0.9673 - val_loss: 0.2078 - val_categorical_accuracy: 0.9359 - 873ms/epoch - 6ms/step
Epoch 180/250
141/141 - 1s - loss: 0.1198 - categorical_accuracy: 0.9616 - val_loss: 0.1726 - val_categorical_accuracy: 0.9450 - 861ms/epoch - 6ms/step
Epoch 181/250
141/141 - 1s - loss: 0.0946 - categorical_accuracy: 0.9678 - val_loss: 0.2315 - val_categorical_accuracy: 0.9294 - 877ms/epoch - 6ms/step
Epoch 182/250
141/141 - 1s - loss: 0.1087 - categorical_accuracy: 0.9631 - val_loss: 0.1811 - val_categorical_accuracy: 0.9411 - 875ms/epoch - 6ms/step
Epoch 183/250
141/141 - 1s - loss: 0.0942 - categorical_accuracy: 0.9679 - val_loss: 0.1886 - val_categorical_accuracy: 0.9383 - 872ms/epoch - 6ms/step
Epoch 184/250
141/141 - 1s - loss: 0.1193 - categorical_accuracy: 0.9611 - val_loss: 0.1914 - val_categorical_accuracy: 0.9401 - 885ms/epoch - 6ms/step
Epoch 185/250
141/141 - 1s - loss: 0.0979 - categorical_accuracy: 0.9664 - val_loss: 0.1883 - val_categorical_accuracy: 0.9431 - 889ms/epoch - 6ms/step
Epoch 186/250
141/141 - 1s - loss: 0.0974 - categorical_accuracy: 0.9668 - val_loss: 0.1748 - val_categorical_accuracy: 0.9468 - 862ms/epoch - 6ms/step
Epoch 187/250
141/141 - 1s - loss: 0.1084 - categorical_accuracy: 0.9636 - val_loss: 0.1702 - val_categorical_accuracy: 0.9481 - 872ms/epoch - 6ms/step
Epoch 188/250
141/141 - 1s - loss: 0.3433 - categorical_accuracy: 0.9087 - val_loss: 0.2048 - val_categorical_accuracy: 0.9321 - 876ms/epoch - 6ms/step
Epoch 189/250
141/141 - 1s - loss: 0.1097 - categorical_accuracy: 0.9627 - val_loss: 0.1674 - val_categorical_accuracy: 0.9477 - 877ms/epoch - 6ms/step
Epoch 190/250
141/141 - 1s - loss: 0.0943 - categorical_accuracy: 0.9680 - val_loss: 0.1753 - val_categorical_accuracy: 0.9440 - 876ms/epoch - 6ms/step
Epoch 191/250
141/141 - 1s - loss: 0.0939 - categorical_accuracy: 0.9681 - val_loss: 0.1944 - val_categorical_accuracy: 0.9368 - 877ms/epoch - 6ms/step
Epoch 192/250
141/141 - 1s - loss: 0.0976 - categorical_accuracy: 0.9668 - val_loss: 0.1852 - val_categorical_accuracy: 0.9421 - 861ms/epoch - 6ms/step
Epoch 193/250
141/141 - 1s - loss: 0.1108 - categorical_accuracy: 0.9632 - val_loss: 0.1672 - val_categorical_accuracy: 0.9473 - 855ms/epoch - 6ms/step
Epoch 194/250
141/141 - 1s - loss: 0.0889 - categorical_accuracy: 0.9699 - val_loss: 0.2071 - val_categorical_accuracy: 0.9386 - 859ms/epoch - 6ms/step
Epoch 195/250
141/141 - 1s - loss: 0.0936 - categorical_accuracy: 0.9678 - val_loss: 0.2235 - val_categorical_accuracy: 0.9342 - 862ms/epoch - 6ms/step
Epoch 196/250
141/141 - 1s - loss: 0.1236 - categorical_accuracy: 0.9594 - val_loss: 0.2890 - val_categorical_accuracy: 0.9113 - 874ms/epoch - 6ms/step
Epoch 197/250
141/141 - 1s - loss: 0.0926 - categorical_accuracy: 0.9685 - val_loss: 0.1918 - val_categorical_accuracy: 0.9409 - 872ms/epoch - 6ms/step
Epoch 198/250
141/141 - 1s - loss: 0.1263 - categorical_accuracy: 0.9612 - val_loss: 0.1693 - val_categorical_accuracy: 0.9469 - 868ms/epoch - 6ms/step
Epoch 199/250
141/141 - 1s - loss: 0.0874 - categorical_accuracy: 0.9704 - val_loss: 0.1880 - val_categorical_accuracy: 0.9459 - 887ms/epoch - 6ms/step
Epoch 200/250
141/141 - 1s - loss: 0.0924 - categorical_accuracy: 0.9684 - val_loss: 0.2515 - val_categorical_accuracy: 0.9270 - 874ms/epoch - 6ms/step
Epoch 201/250
141/141 - 1s - loss: 0.0924 - categorical_accuracy: 0.9684 - val_loss: 0.1795 - val_categorical_accuracy: 0.9477 - 885ms/epoch - 6ms/step
Epoch 202/250
141/141 - 1s - loss: 0.1599 - categorical_accuracy: 0.9540 - val_loss: 0.1761 - val_categorical_accuracy: 0.9461 - 873ms/epoch - 6ms/step
Epoch 203/250
141/141 - 1s - loss: 0.0893 - categorical_accuracy: 0.9698 - val_loss: 0.2048 - val_categorical_accuracy: 0.9404 - 874ms/epoch - 6ms/step
Epoch 204/250
141/141 - 1s - loss: 0.0893 - categorical_accuracy: 0.9697 - val_loss: 0.1758 - val_categorical_accuracy: 0.9451 - 858ms/epoch - 6ms/step
Epoch 205/250
141/141 - 1s - loss: 0.0850 - categorical_accuracy: 0.9714 - val_loss: 0.1786 - val_categorical_accuracy: 0.9477 - 875ms/epoch - 6ms/step
Epoch 206/250
141/141 - 1s - loss: 0.0866 - categorical_accuracy: 0.9704 - val_loss: 0.1743 - val_categorical_accuracy: 0.9478 - 878ms/epoch - 6ms/step
Epoch 207/250
141/141 - 1s - loss: 0.1195 - categorical_accuracy: 0.9618 - val_loss: 0.1797 - val_categorical_accuracy: 0.9437 - 893ms/epoch - 6ms/step
Epoch 208/250
141/141 - 1s - loss: 0.0888 - categorical_accuracy: 0.9698 - val_loss: 0.1801 - val_categorical_accuracy: 0.9448 - 894ms/epoch - 6ms/step
Epoch 209/250
141/141 - 1s - loss: 0.0862 - categorical_accuracy: 0.9707 - val_loss: 0.1749 - val_categorical_accuracy: 0.9464 - 876ms/epoch - 6ms/step
Epoch 210/250
141/141 - 1s - loss: 0.1101 - categorical_accuracy: 0.9646 - val_loss: 0.1776 - val_categorical_accuracy: 0.9470 - 859ms/epoch - 6ms/step
Epoch 211/250
141/141 - 1s - loss: 0.0895 - categorical_accuracy: 0.9696 - val_loss: 0.1762 - val_categorical_accuracy: 0.9484 - 862ms/epoch - 6ms/step
Epoch 212/250
141/141 - 1s - loss: 0.0856 - categorical_accuracy: 0.9709 - val_loss: 0.1867 - val_categorical_accuracy: 0.9442 - 873ms/epoch - 6ms/step
Epoch 213/250
141/141 - 1s - loss: 0.1488 - categorical_accuracy: 0.9562 - val_loss: 0.1865 - val_categorical_accuracy: 0.9417 - 875ms/epoch - 6ms/step
Epoch 214/250
141/141 - 1s - loss: 0.0850 - categorical_accuracy: 0.9713 - val_loss: 0.1788 - val_categorical_accuracy: 0.9451 - 861ms/epoch - 6ms/step
Epoch 215/250
141/141 - 1s - loss: 0.0852 - categorical_accuracy: 0.9708 - val_loss: 0.2451 - val_categorical_accuracy: 0.9280 - 890ms/epoch - 6ms/step
Epoch 216/250
141/141 - 1s - loss: 0.1432 - categorical_accuracy: 0.9578 - val_loss: 0.1851 - val_categorical_accuracy: 0.9456 - 873ms/epoch - 6ms/step
Epoch 217/250
141/141 - 1s - loss: 0.0845 - categorical_accuracy: 0.9715 - val_loss: 0.1646 - val_categorical_accuracy: 0.9516 - 872ms/epoch - 6ms/step
Epoch 218/250
141/141 - 1s - loss: 0.0848 - categorical_accuracy: 0.9712 - val_loss: 0.1803 - val_categorical_accuracy: 0.9441 - 858ms/epoch - 6ms/step
Epoch 219/250
141/141 - 1s - loss: 0.0922 - categorical_accuracy: 0.9687 - val_loss: 0.1888 - val_categorical_accuracy: 0.9380 - 871ms/epoch - 6ms/step
Epoch 220/250
141/141 - 1s - loss: 0.1369 - categorical_accuracy: 0.9579 - val_loss: 0.1842 - val_categorical_accuracy: 0.9443 - 875ms/epoch - 6ms/step
Epoch 221/250
141/141 - 1s - loss: 0.0818 - categorical_accuracy: 0.9722 - val_loss: 0.1760 - val_categorical_accuracy: 0.9464 - 877ms/epoch - 6ms/step
Epoch 222/250
141/141 - 1s - loss: 0.0823 - categorical_accuracy: 0.9720 - val_loss: 0.1925 - val_categorical_accuracy: 0.9453 - 875ms/epoch - 6ms/step
Epoch 223/250
141/141 - 1s - loss: 0.0822 - categorical_accuracy: 0.9718 - val_loss: 0.1823 - val_categorical_accuracy: 0.9455 - 869ms/epoch - 6ms/step
Epoch 224/250
141/141 - 1s - loss: 0.1448 - categorical_accuracy: 0.9574 - val_loss: 0.1902 - val_categorical_accuracy: 0.9428 - 873ms/epoch - 6ms/step
Epoch 225/250
141/141 - 1s - loss: 0.0827 - categorical_accuracy: 0.9720 - val_loss: 0.1633 - val_categorical_accuracy: 0.9510 - 874ms/epoch - 6ms/step
Epoch 226/250
141/141 - 1s - loss: 0.0826 - categorical_accuracy: 0.9719 - val_loss: 0.2040 - val_categorical_accuracy: 0.9389 - 874ms/epoch - 6ms/step
Epoch 227/250
141/141 - 1s - loss: 0.0795 - categorical_accuracy: 0.9733 - val_loss: 0.1722 - val_categorical_accuracy: 0.9502 - 876ms/epoch - 6ms/step
Epoch 228/250
141/141 - 1s - loss: 0.0812 - categorical_accuracy: 0.9725 - val_loss: 0.1776 - val_categorical_accuracy: 0.9476 - 870ms/epoch - 6ms/step
Epoch 229/250
141/141 - 1s - loss: 0.1030 - categorical_accuracy: 0.9668 - val_loss: 1.8504 - val_categorical_accuracy: 0.6624 - 856ms/epoch - 6ms/step
Epoch 230/250
141/141 - 1s - loss: 0.1474 - categorical_accuracy: 0.9568 - val_loss: 0.1646 - val_categorical_accuracy: 0.9513 - 892ms/epoch - 6ms/step
Epoch 231/250
141/141 - 1s - loss: 0.0829 - categorical_accuracy: 0.9719 - val_loss: 0.1903 - val_categorical_accuracy: 0.9445 - 892ms/epoch - 6ms/step
Epoch 232/250
141/141 - 1s - loss: 0.0925 - categorical_accuracy: 0.9690 - val_loss: 0.1795 - val_categorical_accuracy: 0.9447 - 860ms/epoch - 6ms/step
Epoch 233/250
141/141 - 1s - loss: 0.0780 - categorical_accuracy: 0.9734 - val_loss: 0.1772 - val_categorical_accuracy: 0.9488 - 870ms/epoch - 6ms/step
Epoch 234/250
141/141 - 1s - loss: 0.1022 - categorical_accuracy: 0.9669 - val_loss: 0.1893 - val_categorical_accuracy: 0.9443 - 872ms/epoch - 6ms/step
Epoch 235/250
141/141 - 1s - loss: 0.0794 - categorical_accuracy: 0.9729 - val_loss: 0.1822 - val_categorical_accuracy: 0.9483 - 872ms/epoch - 6ms/step
Epoch 236/250
141/141 - 1s - loss: 0.0816 - categorical_accuracy: 0.9722 - val_loss: 0.1832 - val_categorical_accuracy: 0.9469 - 875ms/epoch - 6ms/step
Epoch 237/250
141/141 - 1s - loss: 0.0797 - categorical_accuracy: 0.9729 - val_loss: 0.1821 - val_categorical_accuracy: 0.9478 - 860ms/epoch - 6ms/step
Epoch 238/250
141/141 - 1s - loss: 0.0776 - categorical_accuracy: 0.9736 - val_loss: 0.1740 - val_categorical_accuracy: 0.9488 - 893ms/epoch - 6ms/step
Epoch 239/250
141/141 - 1s - loss: 0.1391 - categorical_accuracy: 0.9594 - val_loss: 0.1828 - val_categorical_accuracy: 0.9434 - 885ms/epoch - 6ms/step
Epoch 240/250
141/141 - 1s - loss: 0.0805 - categorical_accuracy: 0.9729 - val_loss: 0.1872 - val_categorical_accuracy: 0.9446 - 874ms/epoch - 6ms/step
Epoch 241/250
141/141 - 1s - loss: 0.0804 - categorical_accuracy: 0.9725 - val_loss: 0.1791 - val_categorical_accuracy: 0.9462 - 877ms/epoch - 6ms/step
Epoch 242/250
141/141 - 1s - loss: 0.1699 - categorical_accuracy: 0.9527 - val_loss: 0.1759 - val_categorical_accuracy: 0.9461 - 877ms/epoch - 6ms/step
Epoch 243/250
141/141 - 1s - loss: 0.0798 - categorical_accuracy: 0.9730 - val_loss: 0.1853 - val_categorical_accuracy: 0.9451 - 860ms/epoch - 6ms/step
Epoch 244/250
141/141 - 1s - loss: 0.0753 - categorical_accuracy: 0.9746 - val_loss: 0.1783 - val_categorical_accuracy: 0.9493 - 879ms/epoch - 6ms/step
Epoch 245/250
141/141 - 1s - loss: 0.1217 - categorical_accuracy: 0.9632 - val_loss: 0.1944 - val_categorical_accuracy: 0.9395 - 877ms/epoch - 6ms/step
Epoch 246/250
141/141 - 1s - loss: 0.0767 - categorical_accuracy: 0.9742 - val_loss: 0.1957 - val_categorical_accuracy: 0.9406 - 875ms/epoch - 6ms/step
Epoch 247/250
141/141 - 1s - loss: 0.0772 - categorical_accuracy: 0.9737 - val_loss: 0.1644 - val_categorical_accuracy: 0.9530 - 877ms/epoch - 6ms/step
Epoch 248/250
141/141 - 1s - loss: 0.0752 - categorical_accuracy: 0.9745 - val_loss: 0.1785 - val_categorical_accuracy: 0.9486 - 877ms/epoch - 6ms/step
Epoch 249/250
141/141 - 1s - loss: 0.0784 - categorical_accuracy: 0.9734 - val_loss: 0.1823 - val_categorical_accuracy: 0.9465 - 877ms/epoch - 6ms/step
Epoch 250/250
141/141 - 1s - loss: 0.0821 - categorical_accuracy: 0.9719 - val_loss: 0.1742 - val_categorical_accuracy: 0.9509 - 878ms/epoch - 6ms/step
processing fold # 5 
Epoch 1/250
141/141 - 2s - loss: 1.9613 - categorical_accuracy: 0.2654 - val_loss: 1.7357 - val_categorical_accuracy: 0.3284 - 2s/epoch - 12ms/step
Epoch 2/250
141/141 - 1s - loss: 1.5986 - categorical_accuracy: 0.4049 - val_loss: 1.3778 - val_categorical_accuracy: 0.4753 - 923ms/epoch - 7ms/step
Epoch 3/250
141/141 - 1s - loss: 1.3309 - categorical_accuracy: 0.5033 - val_loss: 1.1320 - val_categorical_accuracy: 0.5700 - 873ms/epoch - 6ms/step
Epoch 4/250
141/141 - 1s - loss: 1.1473 - categorical_accuracy: 0.5676 - val_loss: 1.2423 - val_categorical_accuracy: 0.5224 - 876ms/epoch - 6ms/step
Epoch 5/250
141/141 - 1s - loss: 1.0789 - categorical_accuracy: 0.6031 - val_loss: 0.9751 - val_categorical_accuracy: 0.6278 - 862ms/epoch - 6ms/step
Epoch 6/250
141/141 - 1s - loss: 0.9515 - categorical_accuracy: 0.6479 - val_loss: 1.1109 - val_categorical_accuracy: 0.5964 - 877ms/epoch - 6ms/step
Epoch 7/250
141/141 - 1s - loss: 1.0586 - categorical_accuracy: 0.6367 - val_loss: 2.0704 - val_categorical_accuracy: 0.1493 - 874ms/epoch - 6ms/step
Epoch 8/250
141/141 - 1s - loss: 1.7402 - categorical_accuracy: 0.3444 - val_loss: 1.2829 - val_categorical_accuracy: 0.5218 - 862ms/epoch - 6ms/step
Epoch 9/250
141/141 - 1s - loss: 1.1532 - categorical_accuracy: 0.5767 - val_loss: 0.8970 - val_categorical_accuracy: 0.6615 - 875ms/epoch - 6ms/step
Epoch 10/250
141/141 - 1s - loss: 0.9159 - categorical_accuracy: 0.6617 - val_loss: 0.8915 - val_categorical_accuracy: 0.6757 - 873ms/epoch - 6ms/step
Epoch 11/250
141/141 - 1s - loss: 0.7656 - categorical_accuracy: 0.7126 - val_loss: 1.1014 - val_categorical_accuracy: 0.6298 - 876ms/epoch - 6ms/step
Epoch 12/250
141/141 - 1s - loss: 0.7117 - categorical_accuracy: 0.7347 - val_loss: 0.6468 - val_categorical_accuracy: 0.7506 - 893ms/epoch - 6ms/step
Epoch 13/250
141/141 - 1s - loss: 0.6598 - categorical_accuracy: 0.7529 - val_loss: 0.6228 - val_categorical_accuracy: 0.7672 - 859ms/epoch - 6ms/step
Epoch 14/250
141/141 - 1s - loss: 0.6731 - categorical_accuracy: 0.7545 - val_loss: 0.6037 - val_categorical_accuracy: 0.7772 - 861ms/epoch - 6ms/step
Epoch 15/250
141/141 - 1s - loss: 0.5893 - categorical_accuracy: 0.7814 - val_loss: 0.5648 - val_categorical_accuracy: 0.7863 - 859ms/epoch - 6ms/step
Epoch 16/250
141/141 - 1s - loss: 0.5663 - categorical_accuracy: 0.7908 - val_loss: 0.4984 - val_categorical_accuracy: 0.8149 - 857ms/epoch - 6ms/step
Epoch 17/250
141/141 - 1s - loss: 0.5990 - categorical_accuracy: 0.7850 - val_loss: 0.5306 - val_categorical_accuracy: 0.8052 - 876ms/epoch - 6ms/step
Epoch 18/250
141/141 - 1s - loss: 0.5117 - categorical_accuracy: 0.8106 - val_loss: 0.4622 - val_categorical_accuracy: 0.8276 - 875ms/epoch - 6ms/step
Epoch 19/250
141/141 - 1s - loss: 0.4769 - categorical_accuracy: 0.8228 - val_loss: 0.4394 - val_categorical_accuracy: 0.8361 - 884ms/epoch - 6ms/step
Epoch 20/250
141/141 - 1s - loss: 0.6744 - categorical_accuracy: 0.7761 - val_loss: 0.4812 - val_categorical_accuracy: 0.8219 - 856ms/epoch - 6ms/step
Epoch 21/250
141/141 - 1s - loss: 0.4658 - categorical_accuracy: 0.8298 - val_loss: 0.4369 - val_categorical_accuracy: 0.8379 - 846ms/epoch - 6ms/step
Epoch 22/250
141/141 - 1s - loss: 0.4297 - categorical_accuracy: 0.8416 - val_loss: 0.4816 - val_categorical_accuracy: 0.8127 - 858ms/epoch - 6ms/step
Epoch 23/250
141/141 - 1s - loss: 0.5608 - categorical_accuracy: 0.8114 - val_loss: 0.3949 - val_categorical_accuracy: 0.8587 - 892ms/epoch - 6ms/step
Epoch 24/250
141/141 - 1s - loss: 0.4016 - categorical_accuracy: 0.8531 - val_loss: 0.4208 - val_categorical_accuracy: 0.8430 - 867ms/epoch - 6ms/step
Epoch 25/250
141/141 - 1s - loss: 0.3908 - categorical_accuracy: 0.8577 - val_loss: 0.3812 - val_categorical_accuracy: 0.8583 - 858ms/epoch - 6ms/step
Epoch 26/250
141/141 - 1s - loss: 0.3903 - categorical_accuracy: 0.8575 - val_loss: 0.4401 - val_categorical_accuracy: 0.8386 - 861ms/epoch - 6ms/step
Epoch 27/250
141/141 - 1s - loss: 0.4050 - categorical_accuracy: 0.8582 - val_loss: 0.3453 - val_categorical_accuracy: 0.8762 - 895ms/epoch - 6ms/step
Epoch 28/250
141/141 - 1s - loss: 0.3559 - categorical_accuracy: 0.8694 - val_loss: 0.5238 - val_categorical_accuracy: 0.8149 - 863ms/epoch - 6ms/step
Epoch 29/250
141/141 - 1s - loss: 0.3710 - categorical_accuracy: 0.8676 - val_loss: 0.4226 - val_categorical_accuracy: 0.8403 - 859ms/epoch - 6ms/step
Epoch 30/250
141/141 - 1s - loss: 0.3415 - categorical_accuracy: 0.8757 - val_loss: 0.4118 - val_categorical_accuracy: 0.8461 - 879ms/epoch - 6ms/step
Epoch 31/250
141/141 - 1s - loss: 0.3340 - categorical_accuracy: 0.8785 - val_loss: 0.4417 - val_categorical_accuracy: 0.8347 - 876ms/epoch - 6ms/step
Epoch 32/250
141/141 - 1s - loss: 0.4202 - categorical_accuracy: 0.8598 - val_loss: 0.3718 - val_categorical_accuracy: 0.8636 - 874ms/epoch - 6ms/step
Epoch 33/250
141/141 - 1s - loss: 0.3152 - categorical_accuracy: 0.8861 - val_loss: 0.3374 - val_categorical_accuracy: 0.8799 - 860ms/epoch - 6ms/step
Epoch 34/250
141/141 - 1s - loss: 0.3065 - categorical_accuracy: 0.8893 - val_loss: 0.4491 - val_categorical_accuracy: 0.8435 - 878ms/epoch - 6ms/step
Epoch 35/250
141/141 - 1s - loss: 0.3045 - categorical_accuracy: 0.8908 - val_loss: 0.3209 - val_categorical_accuracy: 0.8825 - 875ms/epoch - 6ms/step
Epoch 36/250
141/141 - 1s - loss: 0.3137 - categorical_accuracy: 0.8896 - val_loss: 0.2984 - val_categorical_accuracy: 0.8930 - 876ms/epoch - 6ms/step
Epoch 37/250
141/141 - 1s - loss: 0.2892 - categorical_accuracy: 0.8954 - val_loss: 0.3360 - val_categorical_accuracy: 0.8751 - 1s/epoch - 7ms/step
Epoch 38/250
141/141 - 1s - loss: 0.2864 - categorical_accuracy: 0.8980 - val_loss: 0.2862 - val_categorical_accuracy: 0.8964 - 877ms/epoch - 6ms/step
Epoch 39/250
141/141 - 1s - loss: 0.2753 - categorical_accuracy: 0.9013 - val_loss: 0.3150 - val_categorical_accuracy: 0.8836 - 872ms/epoch - 6ms/step
Epoch 40/250
141/141 - 1s - loss: 0.2926 - categorical_accuracy: 0.8972 - val_loss: 0.3295 - val_categorical_accuracy: 0.8780 - 860ms/epoch - 6ms/step
Epoch 41/250
141/141 - 1s - loss: 0.3123 - categorical_accuracy: 0.8930 - val_loss: 0.3104 - val_categorical_accuracy: 0.8931 - 876ms/epoch - 6ms/step
Epoch 42/250
141/141 - 1s - loss: 0.2627 - categorical_accuracy: 0.9070 - val_loss: 0.2896 - val_categorical_accuracy: 0.8954 - 876ms/epoch - 6ms/step
Epoch 43/250
141/141 - 1s - loss: 0.2546 - categorical_accuracy: 0.9091 - val_loss: 0.2533 - val_categorical_accuracy: 0.9106 - 873ms/epoch - 6ms/step
Epoch 44/250
141/141 - 1s - loss: 0.2554 - categorical_accuracy: 0.9083 - val_loss: 0.3744 - val_categorical_accuracy: 0.8634 - 861ms/epoch - 6ms/step
Epoch 45/250
141/141 - 1s - loss: 0.2471 - categorical_accuracy: 0.9120 - val_loss: 0.3020 - val_categorical_accuracy: 0.8919 - 862ms/epoch - 6ms/step
Epoch 46/250
141/141 - 1s - loss: 0.2654 - categorical_accuracy: 0.9076 - val_loss: 0.3231 - val_categorical_accuracy: 0.8866 - 874ms/epoch - 6ms/step
Epoch 47/250
141/141 - 1s - loss: 0.2375 - categorical_accuracy: 0.9148 - val_loss: 0.3082 - val_categorical_accuracy: 0.8952 - 862ms/epoch - 6ms/step
Epoch 48/250
141/141 - 1s - loss: 0.2383 - categorical_accuracy: 0.9150 - val_loss: 0.2492 - val_categorical_accuracy: 0.9112 - 873ms/epoch - 6ms/step
Epoch 49/250
141/141 - 1s - loss: 0.2270 - categorical_accuracy: 0.9196 - val_loss: 0.2455 - val_categorical_accuracy: 0.9126 - 856ms/epoch - 6ms/step
Epoch 50/250
141/141 - 1s - loss: 0.2484 - categorical_accuracy: 0.9141 - val_loss: 0.2572 - val_categorical_accuracy: 0.9077 - 870ms/epoch - 6ms/step
Epoch 51/250
141/141 - 1s - loss: 0.2526 - categorical_accuracy: 0.9146 - val_loss: 0.2210 - val_categorical_accuracy: 0.9235 - 873ms/epoch - 6ms/step
Epoch 52/250
141/141 - 1s - loss: 0.2215 - categorical_accuracy: 0.9212 - val_loss: 0.2212 - val_categorical_accuracy: 0.9216 - 889ms/epoch - 6ms/step
Epoch 53/250
141/141 - 1s - loss: 0.2316 - categorical_accuracy: 0.9189 - val_loss: 0.2275 - val_categorical_accuracy: 0.9198 - 875ms/epoch - 6ms/step
Epoch 54/250
141/141 - 1s - loss: 0.2138 - categorical_accuracy: 0.9255 - val_loss: 0.2620 - val_categorical_accuracy: 0.9089 - 861ms/epoch - 6ms/step
Epoch 55/250
141/141 - 1s - loss: 0.2153 - categorical_accuracy: 0.9234 - val_loss: 0.2619 - val_categorical_accuracy: 0.9080 - 875ms/epoch - 6ms/step
Epoch 56/250
141/141 - 1s - loss: 0.2103 - categorical_accuracy: 0.9254 - val_loss: 0.2403 - val_categorical_accuracy: 0.9166 - 859ms/epoch - 6ms/step
Epoch 57/250
141/141 - 1s - loss: 0.2131 - categorical_accuracy: 0.9254 - val_loss: 0.2394 - val_categorical_accuracy: 0.9159 - 857ms/epoch - 6ms/step
Epoch 58/250
141/141 - 1s - loss: 0.2042 - categorical_accuracy: 0.9280 - val_loss: 0.2097 - val_categorical_accuracy: 0.9274 - 877ms/epoch - 6ms/step
Epoch 59/250
141/141 - 1s - loss: 0.2713 - categorical_accuracy: 0.9132 - val_loss: 0.2243 - val_categorical_accuracy: 0.9221 - 876ms/epoch - 6ms/step
Epoch 60/250
141/141 - 1s - loss: 0.1949 - categorical_accuracy: 0.9319 - val_loss: 0.2115 - val_categorical_accuracy: 0.9275 - 876ms/epoch - 6ms/step
Epoch 61/250
141/141 - 1s - loss: 0.1954 - categorical_accuracy: 0.9312 - val_loss: 0.2232 - val_categorical_accuracy: 0.9225 - 874ms/epoch - 6ms/step
Epoch 62/250
141/141 - 1s - loss: 0.1904 - categorical_accuracy: 0.9330 - val_loss: 0.2044 - val_categorical_accuracy: 0.9297 - 877ms/epoch - 6ms/step
Epoch 63/250
141/141 - 1s - loss: 0.1939 - categorical_accuracy: 0.9322 - val_loss: 0.7093 - val_categorical_accuracy: 0.7862 - 859ms/epoch - 6ms/step
Epoch 64/250
141/141 - 1s - loss: 0.2851 - categorical_accuracy: 0.9134 - val_loss: 0.2191 - val_categorical_accuracy: 0.9237 - 845ms/epoch - 6ms/step
Epoch 65/250
141/141 - 1s - loss: 0.1874 - categorical_accuracy: 0.9345 - val_loss: 0.2165 - val_categorical_accuracy: 0.9242 - 889ms/epoch - 6ms/step
Epoch 66/250
141/141 - 1s - loss: 0.1812 - categorical_accuracy: 0.9361 - val_loss: 0.1914 - val_categorical_accuracy: 0.9352 - 877ms/epoch - 6ms/step
Epoch 67/250
141/141 - 1s - loss: 0.1865 - categorical_accuracy: 0.9349 - val_loss: 0.2719 - val_categorical_accuracy: 0.9068 - 875ms/epoch - 6ms/step
Epoch 68/250
141/141 - 1s - loss: 0.1899 - categorical_accuracy: 0.9334 - val_loss: 0.2054 - val_categorical_accuracy: 0.9282 - 891ms/epoch - 6ms/step
Epoch 69/250
141/141 - 1s - loss: 0.1743 - categorical_accuracy: 0.9393 - val_loss: 0.2042 - val_categorical_accuracy: 0.9274 - 861ms/epoch - 6ms/step
Epoch 70/250
141/141 - 1s - loss: 0.2050 - categorical_accuracy: 0.9315 - val_loss: 0.2151 - val_categorical_accuracy: 0.9269 - 872ms/epoch - 6ms/step
Epoch 71/250
141/141 - 1s - loss: 0.1754 - categorical_accuracy: 0.9384 - val_loss: 0.2380 - val_categorical_accuracy: 0.9185 - 871ms/epoch - 6ms/step
Epoch 72/250
141/141 - 1s - loss: 0.1794 - categorical_accuracy: 0.9377 - val_loss: 0.1903 - val_categorical_accuracy: 0.9340 - 863ms/epoch - 6ms/step
Epoch 73/250
141/141 - 1s - loss: 0.1760 - categorical_accuracy: 0.9394 - val_loss: 0.2157 - val_categorical_accuracy: 0.9233 - 871ms/epoch - 6ms/step
Epoch 74/250
141/141 - 1s - loss: 0.1709 - categorical_accuracy: 0.9405 - val_loss: 0.1947 - val_categorical_accuracy: 0.9325 - 863ms/epoch - 6ms/step
Epoch 75/250
141/141 - 1s - loss: 0.1575 - categorical_accuracy: 0.9456 - val_loss: 0.1995 - val_categorical_accuracy: 0.9302 - 879ms/epoch - 6ms/step
Epoch 76/250
141/141 - 1s - loss: 0.2330 - categorical_accuracy: 0.9255 - val_loss: 0.2639 - val_categorical_accuracy: 0.9093 - 879ms/epoch - 6ms/step
Epoch 77/250
141/141 - 1s - loss: 0.1599 - categorical_accuracy: 0.9452 - val_loss: 0.1988 - val_categorical_accuracy: 0.9319 - 863ms/epoch - 6ms/step
Epoch 78/250
141/141 - 1s - loss: 0.1748 - categorical_accuracy: 0.9398 - val_loss: 0.2096 - val_categorical_accuracy: 0.9306 - 876ms/epoch - 6ms/step
Epoch 79/250
141/141 - 1s - loss: 0.1561 - categorical_accuracy: 0.9455 - val_loss: 0.2079 - val_categorical_accuracy: 0.9272 - 861ms/epoch - 6ms/step
Epoch 80/250
141/141 - 1s - loss: 0.1545 - categorical_accuracy: 0.9464 - val_loss: 0.1822 - val_categorical_accuracy: 0.9383 - 874ms/epoch - 6ms/step
Epoch 81/250
141/141 - 1s - loss: 0.1673 - categorical_accuracy: 0.9420 - val_loss: 0.7114 - val_categorical_accuracy: 0.8022 - 871ms/epoch - 6ms/step
Epoch 82/250
141/141 - 1s - loss: 0.2502 - categorical_accuracy: 0.9234 - val_loss: 0.1903 - val_categorical_accuracy: 0.9358 - 874ms/epoch - 6ms/step
Epoch 83/250
141/141 - 1s - loss: 0.1633 - categorical_accuracy: 0.9452 - val_loss: 0.1773 - val_categorical_accuracy: 0.9409 - 874ms/epoch - 6ms/step
Epoch 84/250
141/141 - 1s - loss: 0.1475 - categorical_accuracy: 0.9492 - val_loss: 0.2078 - val_categorical_accuracy: 0.9301 - 877ms/epoch - 6ms/step
Epoch 85/250
141/141 - 1s - loss: 0.1751 - categorical_accuracy: 0.9434 - val_loss: 0.1988 - val_categorical_accuracy: 0.9328 - 861ms/epoch - 6ms/step
Epoch 86/250
141/141 - 1s - loss: 0.1536 - categorical_accuracy: 0.9465 - val_loss: 0.1853 - val_categorical_accuracy: 0.9373 - 861ms/epoch - 6ms/step
Epoch 87/250
141/141 - 1s - loss: 0.1447 - categorical_accuracy: 0.9496 - val_loss: 0.2281 - val_categorical_accuracy: 0.9266 - 858ms/epoch - 6ms/step
Epoch 88/250
141/141 - 1s - loss: 0.1493 - categorical_accuracy: 0.9488 - val_loss: 0.2842 - val_categorical_accuracy: 0.9108 - 872ms/epoch - 6ms/step
Epoch 89/250
141/141 - 1s - loss: 0.1443 - categorical_accuracy: 0.9499 - val_loss: 0.1927 - val_categorical_accuracy: 0.9321 - 861ms/epoch - 6ms/step
Epoch 90/250
141/141 - 1s - loss: 0.1400 - categorical_accuracy: 0.9515 - val_loss: 0.2239 - val_categorical_accuracy: 0.9236 - 891ms/epoch - 6ms/step
Epoch 91/250
141/141 - 1s - loss: 0.1513 - categorical_accuracy: 0.9489 - val_loss: 0.2030 - val_categorical_accuracy: 0.9284 - 877ms/epoch - 6ms/step
Epoch 92/250
141/141 - 1s - loss: 0.1385 - categorical_accuracy: 0.9523 - val_loss: 0.1741 - val_categorical_accuracy: 0.9404 - 861ms/epoch - 6ms/step
Epoch 93/250
141/141 - 1s - loss: 0.1492 - categorical_accuracy: 0.9485 - val_loss: 0.1739 - val_categorical_accuracy: 0.9394 - 861ms/epoch - 6ms/step
Epoch 94/250
141/141 - 1s - loss: 0.2176 - categorical_accuracy: 0.9343 - val_loss: 0.1901 - val_categorical_accuracy: 0.9363 - 845ms/epoch - 6ms/step
Epoch 95/250
141/141 - 1s - loss: 0.1293 - categorical_accuracy: 0.9562 - val_loss: 0.1785 - val_categorical_accuracy: 0.9380 - 859ms/epoch - 6ms/step
Epoch 96/250
141/141 - 1s - loss: 0.1449 - categorical_accuracy: 0.9512 - val_loss: 0.1690 - val_categorical_accuracy: 0.9434 - 860ms/epoch - 6ms/step
Epoch 97/250
141/141 - 1s - loss: 0.1371 - categorical_accuracy: 0.9525 - val_loss: 0.1754 - val_categorical_accuracy: 0.9415 - 862ms/epoch - 6ms/step
Epoch 98/250
141/141 - 1s - loss: 0.1487 - categorical_accuracy: 0.9498 - val_loss: 0.1680 - val_categorical_accuracy: 0.9432 - 861ms/epoch - 6ms/step
Epoch 99/250
141/141 - 1s - loss: 0.1272 - categorical_accuracy: 0.9562 - val_loss: 0.1694 - val_categorical_accuracy: 0.9441 - 879ms/epoch - 6ms/step
Epoch 100/250
141/141 - 1s - loss: 0.1300 - categorical_accuracy: 0.9553 - val_loss: 0.2294 - val_categorical_accuracy: 0.9237 - 873ms/epoch - 6ms/step
Epoch 101/250
141/141 - 1s - loss: 0.1572 - categorical_accuracy: 0.9477 - val_loss: 0.2024 - val_categorical_accuracy: 0.9327 - 855ms/epoch - 6ms/step
Epoch 102/250
141/141 - 1s - loss: 0.1224 - categorical_accuracy: 0.9581 - val_loss: 0.1824 - val_categorical_accuracy: 0.9426 - 855ms/epoch - 6ms/step
Epoch 103/250
141/141 - 1s - loss: 0.1405 - categorical_accuracy: 0.9519 - val_loss: 0.1769 - val_categorical_accuracy: 0.9406 - 856ms/epoch - 6ms/step
Epoch 104/250
141/141 - 1s - loss: 0.1318 - categorical_accuracy: 0.9546 - val_loss: 0.1959 - val_categorical_accuracy: 0.9365 - 877ms/epoch - 6ms/step
Epoch 105/250
141/141 - 1s - loss: 0.1201 - categorical_accuracy: 0.9585 - val_loss: 0.1807 - val_categorical_accuracy: 0.9428 - 874ms/epoch - 6ms/step
Epoch 106/250
141/141 - 1s - loss: 0.1398 - categorical_accuracy: 0.9533 - val_loss: 0.1932 - val_categorical_accuracy: 0.9353 - 894ms/epoch - 6ms/step
Epoch 107/250
141/141 - 1s - loss: 0.1311 - categorical_accuracy: 0.9548 - val_loss: 0.1727 - val_categorical_accuracy: 0.9414 - 878ms/epoch - 6ms/step
Epoch 108/250
141/141 - 1s - loss: 0.1180 - categorical_accuracy: 0.9592 - val_loss: 0.2074 - val_categorical_accuracy: 0.9322 - 860ms/epoch - 6ms/step
Epoch 109/250
141/141 - 1s - loss: 0.9720 - categorical_accuracy: 0.7647 - val_loss: 1.6287 - val_categorical_accuracy: 0.3990 - 862ms/epoch - 6ms/step
Epoch 110/250
141/141 - 1s - loss: 1.1530 - categorical_accuracy: 0.5783 - val_loss: 0.8963 - val_categorical_accuracy: 0.6693 - 863ms/epoch - 6ms/step
Epoch 111/250
141/141 - 1s - loss: 0.7891 - categorical_accuracy: 0.7094 - val_loss: 0.6975 - val_categorical_accuracy: 0.7411 - 860ms/epoch - 6ms/step
Epoch 112/250
141/141 - 1s - loss: 0.6247 - categorical_accuracy: 0.7661 - val_loss: 0.5638 - val_categorical_accuracy: 0.7875 - 859ms/epoch - 6ms/step
Epoch 113/250
141/141 - 1s - loss: 0.5531 - categorical_accuracy: 0.7931 - val_loss: 0.5507 - val_categorical_accuracy: 0.7923 - 877ms/epoch - 6ms/step
Epoch 114/250
141/141 - 1s - loss: 0.5050 - categorical_accuracy: 0.8123 - val_loss: 0.4805 - val_categorical_accuracy: 0.8222 - 845ms/epoch - 6ms/step
Epoch 115/250
141/141 - 1s - loss: 0.4634 - categorical_accuracy: 0.8282 - val_loss: 0.4500 - val_categorical_accuracy: 0.8311 - 857ms/epoch - 6ms/step
Epoch 116/250
141/141 - 1s - loss: 0.4333 - categorical_accuracy: 0.8400 - val_loss: 0.4756 - val_categorical_accuracy: 0.8191 - 859ms/epoch - 6ms/step
Epoch 117/250
141/141 - 1s - loss: 0.5394 - categorical_accuracy: 0.8177 - val_loss: 0.4103 - val_categorical_accuracy: 0.8503 - 877ms/epoch - 6ms/step
Epoch 118/250
141/141 - 1s - loss: 0.3935 - categorical_accuracy: 0.8566 - val_loss: 0.4145 - val_categorical_accuracy: 0.8534 - 846ms/epoch - 6ms/step
Epoch 119/250
141/141 - 1s - loss: 0.3677 - categorical_accuracy: 0.8665 - val_loss: 0.4258 - val_categorical_accuracy: 0.8426 - 877ms/epoch - 6ms/step
Epoch 120/250
141/141 - 1s - loss: 0.3944 - categorical_accuracy: 0.8612 - val_loss: 0.3594 - val_categorical_accuracy: 0.8714 - 875ms/epoch - 6ms/step
Epoch 121/250
141/141 - 1s - loss: 0.3374 - categorical_accuracy: 0.8780 - val_loss: 0.3400 - val_categorical_accuracy: 0.8776 - 877ms/epoch - 6ms/step
Epoch 122/250
141/141 - 1s - loss: 0.3255 - categorical_accuracy: 0.8834 - val_loss: 0.3950 - val_categorical_accuracy: 0.8587 - 859ms/epoch - 6ms/step
Epoch 123/250
141/141 - 1s - loss: 0.3209 - categorical_accuracy: 0.8841 - val_loss: 0.3258 - val_categorical_accuracy: 0.8839 - 878ms/epoch - 6ms/step
Epoch 124/250
141/141 - 1s - loss: 0.3132 - categorical_accuracy: 0.8877 - val_loss: 0.3477 - val_categorical_accuracy: 0.8740 - 862ms/epoch - 6ms/step
Epoch 125/250
141/141 - 1s - loss: 0.2987 - categorical_accuracy: 0.8932 - val_loss: 0.3384 - val_categorical_accuracy: 0.8797 - 859ms/epoch - 6ms/step
Epoch 126/250
141/141 - 1s - loss: 0.5565 - categorical_accuracy: 0.8206 - val_loss: 0.3352 - val_categorical_accuracy: 0.8813 - 874ms/epoch - 6ms/step
Epoch 127/250
141/141 - 1s - loss: 0.2917 - categorical_accuracy: 0.8965 - val_loss: 0.3635 - val_categorical_accuracy: 0.8705 - 879ms/epoch - 6ms/step
Epoch 128/250
141/141 - 1s - loss: 0.2787 - categorical_accuracy: 0.9008 - val_loss: 0.3203 - val_categorical_accuracy: 0.8836 - 876ms/epoch - 6ms/step
Epoch 129/250
141/141 - 1s - loss: 0.2924 - categorical_accuracy: 0.8985 - val_loss: 0.3046 - val_categorical_accuracy: 0.8904 - 869ms/epoch - 6ms/step
Epoch 130/250
141/141 - 1s - loss: 0.2610 - categorical_accuracy: 0.9064 - val_loss: 0.3060 - val_categorical_accuracy: 0.8919 - 856ms/epoch - 6ms/step
Epoch 131/250
141/141 - 1s - loss: 0.2611 - categorical_accuracy: 0.9072 - val_loss: 0.3171 - val_categorical_accuracy: 0.8857 - 877ms/epoch - 6ms/step
Epoch 132/250
141/141 - 1s - loss: 0.2811 - categorical_accuracy: 0.9036 - val_loss: 0.2844 - val_categorical_accuracy: 0.8991 - 861ms/epoch - 6ms/step
Epoch 133/250
141/141 - 1s - loss: 0.2445 - categorical_accuracy: 0.9129 - val_loss: 0.2731 - val_categorical_accuracy: 0.9026 - 860ms/epoch - 6ms/step
Epoch 134/250
141/141 - 1s - loss: 0.2463 - categorical_accuracy: 0.9127 - val_loss: 0.2927 - val_categorical_accuracy: 0.8958 - 860ms/epoch - 6ms/step
Epoch 135/250
141/141 - 1s - loss: 0.2364 - categorical_accuracy: 0.9161 - val_loss: 0.4073 - val_categorical_accuracy: 0.8628 - 878ms/epoch - 6ms/step
Epoch 136/250
141/141 - 1s - loss: 0.2342 - categorical_accuracy: 0.9179 - val_loss: 0.2802 - val_categorical_accuracy: 0.9032 - 863ms/epoch - 6ms/step
Epoch 137/250
141/141 - 1s - loss: 0.2423 - categorical_accuracy: 0.9157 - val_loss: 0.3267 - val_categorical_accuracy: 0.8861 - 863ms/epoch - 6ms/step
Epoch 138/250
141/141 - 1s - loss: 0.2286 - categorical_accuracy: 0.9191 - val_loss: 0.2552 - val_categorical_accuracy: 0.9098 - 861ms/epoch - 6ms/step
Epoch 139/250
141/141 - 1s - loss: 0.2190 - categorical_accuracy: 0.9225 - val_loss: 0.2539 - val_categorical_accuracy: 0.9113 - 876ms/epoch - 6ms/step
Epoch 140/250
141/141 - 1s - loss: 0.2388 - categorical_accuracy: 0.9175 - val_loss: 0.2630 - val_categorical_accuracy: 0.9083 - 863ms/epoch - 6ms/step
Epoch 141/250
141/141 - 1s - loss: 0.2080 - categorical_accuracy: 0.9273 - val_loss: 0.2618 - val_categorical_accuracy: 0.9086 - 863ms/epoch - 6ms/step
Epoch 142/250
141/141 - 1s - loss: 0.2136 - categorical_accuracy: 0.9248 - val_loss: 0.2535 - val_categorical_accuracy: 0.9127 - 863ms/epoch - 6ms/step
Epoch 143/250
141/141 - 1s - loss: 0.2993 - categorical_accuracy: 0.9043 - val_loss: 0.2353 - val_categorical_accuracy: 0.9181 - 873ms/epoch - 6ms/step
Epoch 144/250
141/141 - 1s - loss: 0.1996 - categorical_accuracy: 0.9303 - val_loss: 0.2409 - val_categorical_accuracy: 0.9163 - 872ms/epoch - 6ms/step
Epoch 145/250
141/141 - 1s - loss: 0.2134 - categorical_accuracy: 0.9260 - val_loss: 0.2372 - val_categorical_accuracy: 0.9182 - 873ms/epoch - 6ms/step
Epoch 146/250
141/141 - 1s - loss: 0.1965 - categorical_accuracy: 0.9310 - val_loss: 0.2527 - val_categorical_accuracy: 0.9127 - 863ms/epoch - 6ms/step
Epoch 147/250
141/141 - 1s - loss: 0.1966 - categorical_accuracy: 0.9311 - val_loss: 0.2406 - val_categorical_accuracy: 0.9167 - 875ms/epoch - 6ms/step
Epoch 148/250
141/141 - 1s - loss: 0.1959 - categorical_accuracy: 0.9314 - val_loss: 0.2306 - val_categorical_accuracy: 0.9212 - 861ms/epoch - 6ms/step
Epoch 149/250
141/141 - 1s - loss: 0.1971 - categorical_accuracy: 0.9316 - val_loss: 0.2476 - val_categorical_accuracy: 0.9150 - 862ms/epoch - 6ms/step
Epoch 150/250
141/141 - 1s - loss: 0.1888 - categorical_accuracy: 0.9335 - val_loss: 0.2249 - val_categorical_accuracy: 0.9231 - 863ms/epoch - 6ms/step
Epoch 151/250
141/141 - 1s - loss: 0.1847 - categorical_accuracy: 0.9354 - val_loss: 0.2236 - val_categorical_accuracy: 0.9245 - 863ms/epoch - 6ms/step
Epoch 152/250
141/141 - 1s - loss: 0.2111 - categorical_accuracy: 0.9298 - val_loss: 0.2354 - val_categorical_accuracy: 0.9181 - 862ms/epoch - 6ms/step
Epoch 153/250
141/141 - 1s - loss: 0.1816 - categorical_accuracy: 0.9368 - val_loss: 0.2303 - val_categorical_accuracy: 0.9208 - 872ms/epoch - 6ms/step
Epoch 154/250
141/141 - 1s - loss: 0.1825 - categorical_accuracy: 0.9365 - val_loss: 0.2213 - val_categorical_accuracy: 0.9235 - 863ms/epoch - 6ms/step
Epoch 155/250
141/141 - 1s - loss: 0.1794 - categorical_accuracy: 0.9373 - val_loss: 0.2195 - val_categorical_accuracy: 0.9249 - 863ms/epoch - 6ms/step
Epoch 156/250
141/141 - 1s - loss: 0.2173 - categorical_accuracy: 0.9292 - val_loss: 0.3686 - val_categorical_accuracy: 0.8726 - 858ms/epoch - 6ms/step
Epoch 157/250
141/141 - 1s - loss: 0.1720 - categorical_accuracy: 0.9410 - val_loss: 0.2751 - val_categorical_accuracy: 0.9101 - 877ms/epoch - 6ms/step
Epoch 158/250
141/141 - 1s - loss: 0.1703 - categorical_accuracy: 0.9411 - val_loss: 0.2390 - val_categorical_accuracy: 0.9184 - 845ms/epoch - 6ms/step
Epoch 159/250
141/141 - 1s - loss: 0.1688 - categorical_accuracy: 0.9410 - val_loss: 0.2604 - val_categorical_accuracy: 0.9064 - 875ms/epoch - 6ms/step
Epoch 160/250
141/141 - 1s - loss: 0.1672 - categorical_accuracy: 0.9417 - val_loss: 0.2427 - val_categorical_accuracy: 0.9141 - 877ms/epoch - 6ms/step
Epoch 161/250
141/141 - 1s - loss: 0.1772 - categorical_accuracy: 0.9389 - val_loss: 0.2289 - val_categorical_accuracy: 0.9188 - 879ms/epoch - 6ms/step
Epoch 162/250
141/141 - 1s - loss: 0.1664 - categorical_accuracy: 0.9422 - val_loss: 0.2208 - val_categorical_accuracy: 0.9265 - 862ms/epoch - 6ms/step
Epoch 163/250
141/141 - 1s - loss: 0.1609 - categorical_accuracy: 0.9441 - val_loss: 0.1934 - val_categorical_accuracy: 0.9346 - 879ms/epoch - 6ms/step
Epoch 164/250
141/141 - 1s - loss: 0.1910 - categorical_accuracy: 0.9378 - val_loss: 0.2048 - val_categorical_accuracy: 0.9283 - 888ms/epoch - 6ms/step
Epoch 165/250
141/141 - 1s - loss: 0.1600 - categorical_accuracy: 0.9447 - val_loss: 0.2233 - val_categorical_accuracy: 0.9249 - 875ms/epoch - 6ms/step
Epoch 166/250
141/141 - 1s - loss: 0.1531 - categorical_accuracy: 0.9469 - val_loss: 0.2439 - val_categorical_accuracy: 0.9203 - 846ms/epoch - 6ms/step
Epoch 167/250
141/141 - 1s - loss: 0.1757 - categorical_accuracy: 0.9403 - val_loss: 0.2218 - val_categorical_accuracy: 0.9240 - 874ms/epoch - 6ms/step
Epoch 168/250
141/141 - 1s - loss: 0.1514 - categorical_accuracy: 0.9480 - val_loss: 0.2381 - val_categorical_accuracy: 0.9204 - 891ms/epoch - 6ms/step
Epoch 169/250
141/141 - 1s - loss: 0.1579 - categorical_accuracy: 0.9449 - val_loss: 0.1878 - val_categorical_accuracy: 0.9372 - 875ms/epoch - 6ms/step
Epoch 170/250
141/141 - 1s - loss: 0.1834 - categorical_accuracy: 0.9402 - val_loss: 0.1931 - val_categorical_accuracy: 0.9335 - 843ms/epoch - 6ms/step
Epoch 171/250
141/141 - 1s - loss: 0.1469 - categorical_accuracy: 0.9496 - val_loss: 0.2042 - val_categorical_accuracy: 0.9309 - 876ms/epoch - 6ms/step
Epoch 172/250
141/141 - 1s - loss: 0.1489 - categorical_accuracy: 0.9486 - val_loss: 0.3625 - val_categorical_accuracy: 0.8833 - 858ms/epoch - 6ms/step
Epoch 173/250
141/141 - 1s - loss: 0.2127 - categorical_accuracy: 0.9331 - val_loss: 0.2058 - val_categorical_accuracy: 0.9307 - 863ms/epoch - 6ms/step
Epoch 174/250
141/141 - 1s - loss: 0.1437 - categorical_accuracy: 0.9509 - val_loss: 0.1988 - val_categorical_accuracy: 0.9346 - 841ms/epoch - 6ms/step
Epoch 175/250
141/141 - 1s - loss: 0.1389 - categorical_accuracy: 0.9521 - val_loss: 0.1978 - val_categorical_accuracy: 0.9323 - 875ms/epoch - 6ms/step
Epoch 176/250
141/141 - 1s - loss: 0.1385 - categorical_accuracy: 0.9521 - val_loss: 0.2049 - val_categorical_accuracy: 0.9316 - 879ms/epoch - 6ms/step
Epoch 177/250
141/141 - 1s - loss: 0.1469 - categorical_accuracy: 0.9491 - val_loss: 0.2044 - val_categorical_accuracy: 0.9325 - 859ms/epoch - 6ms/step
Epoch 178/250
141/141 - 1s - loss: 0.1411 - categorical_accuracy: 0.9515 - val_loss: 0.2049 - val_categorical_accuracy: 0.9309 - 854ms/epoch - 6ms/step
Epoch 179/250
141/141 - 1s - loss: 0.1645 - categorical_accuracy: 0.9456 - val_loss: 0.1959 - val_categorical_accuracy: 0.9339 - 887ms/epoch - 6ms/step
Epoch 180/250
141/141 - 1s - loss: 0.1375 - categorical_accuracy: 0.9528 - val_loss: 0.2588 - val_categorical_accuracy: 0.9129 - 867ms/epoch - 6ms/step
Epoch 181/250
141/141 - 1s - loss: 0.1380 - categorical_accuracy: 0.9527 - val_loss: 0.1841 - val_categorical_accuracy: 0.9385 - 871ms/epoch - 6ms/step
Epoch 182/250
141/141 - 1s - loss: 0.2482 - categorical_accuracy: 0.9283 - val_loss: 0.2014 - val_categorical_accuracy: 0.9307 - 856ms/epoch - 6ms/step
Epoch 183/250
141/141 - 1s - loss: 0.1320 - categorical_accuracy: 0.9550 - val_loss: 0.1940 - val_categorical_accuracy: 0.9339 - 873ms/epoch - 6ms/step
Epoch 184/250
141/141 - 1s - loss: 0.1320 - categorical_accuracy: 0.9547 - val_loss: 0.2918 - val_categorical_accuracy: 0.9022 - 873ms/epoch - 6ms/step
Epoch 185/250
141/141 - 1s - loss: 0.1347 - categorical_accuracy: 0.9537 - val_loss: 0.2891 - val_categorical_accuracy: 0.9003 - 871ms/epoch - 6ms/step
Epoch 186/250
141/141 - 1s - loss: 0.1587 - categorical_accuracy: 0.9478 - val_loss: 0.1890 - val_categorical_accuracy: 0.9362 - 860ms/epoch - 6ms/step
Epoch 187/250
141/141 - 1s - loss: 0.1310 - categorical_accuracy: 0.9549 - val_loss: 0.1815 - val_categorical_accuracy: 0.9408 - 860ms/epoch - 6ms/step
Epoch 188/250
141/141 - 1s - loss: 0.1263 - categorical_accuracy: 0.9571 - val_loss: 0.2077 - val_categorical_accuracy: 0.9292 - 875ms/epoch - 6ms/step
Epoch 189/250
141/141 - 1s - loss: 0.1414 - categorical_accuracy: 0.9514 - val_loss: 0.1895 - val_categorical_accuracy: 0.9381 - 871ms/epoch - 6ms/step
Epoch 190/250
141/141 - 1s - loss: 0.1381 - categorical_accuracy: 0.9529 - val_loss: 0.2060 - val_categorical_accuracy: 0.9329 - 858ms/epoch - 6ms/step
Epoch 191/250
141/141 - 1s - loss: 0.1293 - categorical_accuracy: 0.9554 - val_loss: 0.2637 - val_categorical_accuracy: 0.9168 - 890ms/epoch - 6ms/step
Epoch 192/250
141/141 - 1s - loss: 0.1331 - categorical_accuracy: 0.9544 - val_loss: 0.1958 - val_categorical_accuracy: 0.9361 - 857ms/epoch - 6ms/step
Epoch 193/250
141/141 - 1s - loss: 0.1351 - categorical_accuracy: 0.9539 - val_loss: 0.1978 - val_categorical_accuracy: 0.9347 - 877ms/epoch - 6ms/step
Epoch 194/250
141/141 - 1s - loss: 0.1244 - categorical_accuracy: 0.9573 - val_loss: 0.2073 - val_categorical_accuracy: 0.9314 - 841ms/epoch - 6ms/step
Epoch 195/250
141/141 - 1s - loss: 0.1284 - categorical_accuracy: 0.9560 - val_loss: 0.1880 - val_categorical_accuracy: 0.9386 - 884ms/epoch - 6ms/step
Epoch 196/250
141/141 - 1s - loss: 0.1755 - categorical_accuracy: 0.9456 - val_loss: 0.1909 - val_categorical_accuracy: 0.9376 - 868ms/epoch - 6ms/step
Epoch 197/250
141/141 - 1s - loss: 0.1206 - categorical_accuracy: 0.9592 - val_loss: 0.1878 - val_categorical_accuracy: 0.9379 - 888ms/epoch - 6ms/step
Epoch 198/250
141/141 - 1s - loss: 0.1201 - categorical_accuracy: 0.9589 - val_loss: 0.2247 - val_categorical_accuracy: 0.9239 - 854ms/epoch - 6ms/step
Epoch 199/250
141/141 - 1s - loss: 0.1195 - categorical_accuracy: 0.9592 - val_loss: 0.3928 - val_categorical_accuracy: 0.8889 - 875ms/epoch - 6ms/step
Epoch 200/250
141/141 - 1s - loss: 0.1580 - categorical_accuracy: 0.9495 - val_loss: 0.1946 - val_categorical_accuracy: 0.9380 - 875ms/epoch - 6ms/step
Epoch 201/250
141/141 - 1s - loss: 0.1301 - categorical_accuracy: 0.9561 - val_loss: 0.1722 - val_categorical_accuracy: 0.9434 - 860ms/epoch - 6ms/step
Epoch 202/250
141/141 - 1s - loss: 0.1132 - categorical_accuracy: 0.9616 - val_loss: 0.1958 - val_categorical_accuracy: 0.9361 - 844ms/epoch - 6ms/step
Epoch 203/250
141/141 - 1s - loss: 0.1172 - categorical_accuracy: 0.9598 - val_loss: 0.1756 - val_categorical_accuracy: 0.9451 - 877ms/epoch - 6ms/step
Epoch 204/250
141/141 - 1s - loss: 0.1496 - categorical_accuracy: 0.9524 - val_loss: 0.1999 - val_categorical_accuracy: 0.9371 - 884ms/epoch - 6ms/step
Epoch 205/250
141/141 - 1s - loss: 0.1165 - categorical_accuracy: 0.9601 - val_loss: 0.2157 - val_categorical_accuracy: 0.9330 - 874ms/epoch - 6ms/step
Epoch 206/250
141/141 - 1s - loss: 0.1184 - categorical_accuracy: 0.9592 - val_loss: 0.2072 - val_categorical_accuracy: 0.9323 - 863ms/epoch - 6ms/step
Epoch 207/250
141/141 - 1s - loss: 0.1231 - categorical_accuracy: 0.9576 - val_loss: 0.1941 - val_categorical_accuracy: 0.9350 - 876ms/epoch - 6ms/step
Epoch 208/250
141/141 - 1s - loss: 0.1588 - categorical_accuracy: 0.9498 - val_loss: 0.1857 - val_categorical_accuracy: 0.9401 - 859ms/epoch - 6ms/step
Epoch 209/250
141/141 - 1s - loss: 0.1105 - categorical_accuracy: 0.9626 - val_loss: 0.2184 - val_categorical_accuracy: 0.9243 - 859ms/epoch - 6ms/step
Epoch 210/250
141/141 - 1s - loss: 0.1103 - categorical_accuracy: 0.9625 - val_loss: 0.3849 - val_categorical_accuracy: 0.8848 - 862ms/epoch - 6ms/step
Epoch 211/250
141/141 - 1s - loss: 0.1437 - categorical_accuracy: 0.9536 - val_loss: 0.1846 - val_categorical_accuracy: 0.9394 - 889ms/epoch - 6ms/step
Epoch 212/250
141/141 - 1s - loss: 0.1069 - categorical_accuracy: 0.9638 - val_loss: 0.1775 - val_categorical_accuracy: 0.9414 - 861ms/epoch - 6ms/step
Epoch 213/250
141/141 - 1s - loss: 0.1141 - categorical_accuracy: 0.9606 - val_loss: 0.3121 - val_categorical_accuracy: 0.8950 - 876ms/epoch - 6ms/step
Epoch 214/250
141/141 - 1s - loss: 0.1155 - categorical_accuracy: 0.9612 - val_loss: 0.1938 - val_categorical_accuracy: 0.9382 - 862ms/epoch - 6ms/step
Epoch 215/250
141/141 - 1s - loss: 0.1791 - categorical_accuracy: 0.9453 - val_loss: 0.1854 - val_categorical_accuracy: 0.9401 - 877ms/epoch - 6ms/step
Epoch 216/250
141/141 - 1s - loss: 0.1071 - categorical_accuracy: 0.9638 - val_loss: 0.1767 - val_categorical_accuracy: 0.9451 - 858ms/epoch - 6ms/step
Epoch 217/250
141/141 - 1s - loss: 0.1055 - categorical_accuracy: 0.9644 - val_loss: 0.1902 - val_categorical_accuracy: 0.9381 - 861ms/epoch - 6ms/step
Epoch 218/250
141/141 - 1s - loss: 0.1344 - categorical_accuracy: 0.9557 - val_loss: 0.1970 - val_categorical_accuracy: 0.9381 - 844ms/epoch - 6ms/step
Epoch 219/250
141/141 - 1s - loss: 0.1040 - categorical_accuracy: 0.9645 - val_loss: 0.2103 - val_categorical_accuracy: 0.9339 - 877ms/epoch - 6ms/step
Epoch 220/250
141/141 - 1s - loss: 0.1070 - categorical_accuracy: 0.9635 - val_loss: 0.2696 - val_categorical_accuracy: 0.9197 - 873ms/epoch - 6ms/step
Epoch 221/250
141/141 - 1s - loss: 0.1200 - categorical_accuracy: 0.9598 - val_loss: 0.1730 - val_categorical_accuracy: 0.9457 - 873ms/epoch - 6ms/step
Epoch 222/250
141/141 - 1s - loss: 0.1050 - categorical_accuracy: 0.9643 - val_loss: 0.1835 - val_categorical_accuracy: 0.9417 - 876ms/epoch - 6ms/step
Epoch 223/250
141/141 - 1s - loss: 0.1056 - categorical_accuracy: 0.9639 - val_loss: 0.1805 - val_categorical_accuracy: 0.9433 - 861ms/epoch - 6ms/step
Epoch 224/250
141/141 - 1s - loss: 0.1056 - categorical_accuracy: 0.9637 - val_loss: 0.2040 - val_categorical_accuracy: 0.9382 - 874ms/epoch - 6ms/step
Epoch 225/250
141/141 - 1s - loss: 0.1051 - categorical_accuracy: 0.9641 - val_loss: 0.2533 - val_categorical_accuracy: 0.9206 - 862ms/epoch - 6ms/step
Epoch 226/250
141/141 - 1s - loss: 0.1024 - categorical_accuracy: 0.9650 - val_loss: 0.2007 - val_categorical_accuracy: 0.9382 - 860ms/epoch - 6ms/step
Epoch 227/250
141/141 - 1s - loss: 0.2425 - categorical_accuracy: 0.9301 - val_loss: 0.2146 - val_categorical_accuracy: 0.9294 - 856ms/epoch - 6ms/step
Epoch 228/250
141/141 - 1s - loss: 0.1147 - categorical_accuracy: 0.9610 - val_loss: 0.1997 - val_categorical_accuracy: 0.9372 - 863ms/epoch - 6ms/step
Epoch 229/250
141/141 - 1s - loss: 0.0994 - categorical_accuracy: 0.9665 - val_loss: 0.1670 - val_categorical_accuracy: 0.9476 - 875ms/epoch - 6ms/step
Epoch 230/250
141/141 - 1s - loss: 0.1140 - categorical_accuracy: 0.9619 - val_loss: 0.2050 - val_categorical_accuracy: 0.9338 - 861ms/epoch - 6ms/step
Epoch 231/250
141/141 - 1s - loss: 0.0992 - categorical_accuracy: 0.9664 - val_loss: 0.1732 - val_categorical_accuracy: 0.9477 - 893ms/epoch - 6ms/step
Epoch 232/250
141/141 - 1s - loss: 0.1026 - categorical_accuracy: 0.9650 - val_loss: 0.1777 - val_categorical_accuracy: 0.9456 - 878ms/epoch - 6ms/step
Epoch 233/250
141/141 - 1s - loss: 0.1006 - categorical_accuracy: 0.9655 - val_loss: 0.1819 - val_categorical_accuracy: 0.9448 - 888ms/epoch - 6ms/step
Epoch 234/250
141/141 - 1s - loss: 0.0991 - categorical_accuracy: 0.9662 - val_loss: 0.1860 - val_categorical_accuracy: 0.9444 - 859ms/epoch - 6ms/step
Epoch 235/250
141/141 - 1s - loss: 0.1205 - categorical_accuracy: 0.9600 - val_loss: 0.1849 - val_categorical_accuracy: 0.9411 - 872ms/epoch - 6ms/step
Epoch 236/250
141/141 - 1s - loss: 0.0948 - categorical_accuracy: 0.9677 - val_loss: 0.2252 - val_categorical_accuracy: 0.9269 - 873ms/epoch - 6ms/step
Epoch 237/250
141/141 - 1s - loss: 0.0961 - categorical_accuracy: 0.9673 - val_loss: 0.1887 - val_categorical_accuracy: 0.9436 - 873ms/epoch - 6ms/step
Epoch 238/250
141/141 - 1s - loss: 0.1787 - categorical_accuracy: 0.9482 - val_loss: 0.1685 - val_categorical_accuracy: 0.9473 - 862ms/epoch - 6ms/step
Epoch 239/250
141/141 - 1s - loss: 0.0938 - categorical_accuracy: 0.9684 - val_loss: 0.1863 - val_categorical_accuracy: 0.9432 - 875ms/epoch - 6ms/step
Epoch 240/250
141/141 - 1s - loss: 0.0983 - categorical_accuracy: 0.9665 - val_loss: 0.1842 - val_categorical_accuracy: 0.9452 - 875ms/epoch - 6ms/step
Epoch 241/250
141/141 - 1s - loss: 0.1273 - categorical_accuracy: 0.9596 - val_loss: 0.1926 - val_categorical_accuracy: 0.9375 - 878ms/epoch - 6ms/step
Epoch 242/250
141/141 - 1s - loss: 0.1066 - categorical_accuracy: 0.9643 - val_loss: 0.2013 - val_categorical_accuracy: 0.9359 - 859ms/epoch - 6ms/step
Epoch 243/250
141/141 - 1s - loss: 0.0928 - categorical_accuracy: 0.9685 - val_loss: 0.1789 - val_categorical_accuracy: 0.9459 - 887ms/epoch - 6ms/step
Epoch 244/250
141/141 - 1s - loss: 0.0980 - categorical_accuracy: 0.9665 - val_loss: 0.1964 - val_categorical_accuracy: 0.9401 - 894ms/epoch - 6ms/step
Epoch 245/250
141/141 - 1s - loss: 0.0923 - categorical_accuracy: 0.9686 - val_loss: 0.2047 - val_categorical_accuracy: 0.9366 - 862ms/epoch - 6ms/step
Epoch 246/250
141/141 - 1s - loss: 0.0964 - categorical_accuracy: 0.9670 - val_loss: 0.1761 - val_categorical_accuracy: 0.9493 - 859ms/epoch - 6ms/step
Epoch 247/250
141/141 - 1s - loss: 0.1174 - categorical_accuracy: 0.9618 - val_loss: 0.1773 - val_categorical_accuracy: 0.9457 - 859ms/epoch - 6ms/step
Epoch 248/250
141/141 - 1s - loss: 0.0951 - categorical_accuracy: 0.9677 - val_loss: 0.1707 - val_categorical_accuracy: 0.9493 - 859ms/epoch - 6ms/step
Epoch 249/250
141/141 - 1s - loss: 0.0890 - categorical_accuracy: 0.9701 - val_loss: 0.1770 - val_categorical_accuracy: 0.9469 - 858ms/epoch - 6ms/step
Epoch 250/250
141/141 - 1s - loss: 0.1237 - categorical_accuracy: 0.9608 - val_loss: 0.2023 - val_categorical_accuracy: 0.9361 - 874ms/epoch - 6ms/step
processing fold # 6 
Epoch 1/250
141/141 - 2s - loss: 1.9397 - categorical_accuracy: 0.2588 - val_loss: 1.7085 - val_categorical_accuracy: 0.3768 - 2s/epoch - 12ms/step
Epoch 2/250
141/141 - 1s - loss: 1.6029 - categorical_accuracy: 0.4018 - val_loss: 1.5172 - val_categorical_accuracy: 0.4526 - 875ms/epoch - 6ms/step
Epoch 3/250
141/141 - 1s - loss: 1.3141 - categorical_accuracy: 0.5030 - val_loss: 1.1763 - val_categorical_accuracy: 0.5651 - 861ms/epoch - 6ms/step
Epoch 4/250
141/141 - 1s - loss: 1.2397 - categorical_accuracy: 0.5396 - val_loss: 1.0209 - val_categorical_accuracy: 0.6233 - 889ms/epoch - 6ms/step
Epoch 5/250
141/141 - 1s - loss: 1.0403 - categorical_accuracy: 0.6102 - val_loss: 0.9317 - val_categorical_accuracy: 0.6533 - 871ms/epoch - 6ms/step
Epoch 6/250
141/141 - 1s - loss: 1.0141 - categorical_accuracy: 0.6275 - val_loss: 0.8789 - val_categorical_accuracy: 0.6750 - 874ms/epoch - 6ms/step
Epoch 7/250
141/141 - 1s - loss: 0.8478 - categorical_accuracy: 0.6826 - val_loss: 1.1737 - val_categorical_accuracy: 0.5721 - 858ms/epoch - 6ms/step
Epoch 8/250
141/141 - 1s - loss: 0.8583 - categorical_accuracy: 0.6882 - val_loss: 1.9011 - val_categorical_accuracy: 0.4445 - 870ms/epoch - 6ms/step
Epoch 9/250
141/141 - 1s - loss: 0.7715 - categorical_accuracy: 0.7178 - val_loss: 0.8333 - val_categorical_accuracy: 0.6940 - 877ms/epoch - 6ms/step
Epoch 10/250
141/141 - 1s - loss: 0.6958 - categorical_accuracy: 0.7442 - val_loss: 0.6072 - val_categorical_accuracy: 0.7742 - 874ms/epoch - 6ms/step
Epoch 11/250
141/141 - 1s - loss: 0.6553 - categorical_accuracy: 0.7599 - val_loss: 0.5751 - val_categorical_accuracy: 0.7870 - 875ms/epoch - 6ms/step
Epoch 12/250
141/141 - 1s - loss: 0.5963 - categorical_accuracy: 0.7785 - val_loss: 0.5661 - val_categorical_accuracy: 0.7873 - 861ms/epoch - 6ms/step
Epoch 13/250
141/141 - 1s - loss: 0.5978 - categorical_accuracy: 0.7804 - val_loss: 0.5328 - val_categorical_accuracy: 0.8048 - 859ms/epoch - 6ms/step
Epoch 14/250
141/141 - 1s - loss: 0.6036 - categorical_accuracy: 0.7846 - val_loss: 0.5017 - val_categorical_accuracy: 0.8164 - 859ms/epoch - 6ms/step
Epoch 15/250
141/141 - 1s - loss: 0.5254 - categorical_accuracy: 0.8081 - val_loss: 0.5383 - val_categorical_accuracy: 0.7991 - 858ms/epoch - 6ms/step
Epoch 16/250
141/141 - 1s - loss: 0.5011 - categorical_accuracy: 0.8159 - val_loss: 0.5203 - val_categorical_accuracy: 0.8070 - 853ms/epoch - 6ms/step
Epoch 17/250
141/141 - 1s - loss: 0.4734 - categorical_accuracy: 0.8257 - val_loss: 0.4682 - val_categorical_accuracy: 0.8291 - 868ms/epoch - 6ms/step
Epoch 18/250
141/141 - 1s - loss: 0.4722 - categorical_accuracy: 0.8275 - val_loss: 0.4633 - val_categorical_accuracy: 0.8205 - 907ms/epoch - 6ms/step
Epoch 19/250
141/141 - 1s - loss: 0.5274 - categorical_accuracy: 0.8166 - val_loss: 0.4711 - val_categorical_accuracy: 0.8208 - 874ms/epoch - 6ms/step
Epoch 20/250
141/141 - 1s - loss: 0.4185 - categorical_accuracy: 0.8453 - val_loss: 0.4047 - val_categorical_accuracy: 0.8495 - 891ms/epoch - 6ms/step
Epoch 21/250
141/141 - 1s - loss: 0.8082 - categorical_accuracy: 0.7313 - val_loss: 0.4912 - val_categorical_accuracy: 0.8281 - 870ms/epoch - 6ms/step
Epoch 22/250
141/141 - 1s - loss: 0.4553 - categorical_accuracy: 0.8360 - val_loss: 0.3847 - val_categorical_accuracy: 0.8592 - 886ms/epoch - 6ms/step
Epoch 23/250
141/141 - 1s - loss: 0.4718 - categorical_accuracy: 0.8361 - val_loss: 0.3871 - val_categorical_accuracy: 0.8611 - 857ms/epoch - 6ms/step
Epoch 24/250
141/141 - 1s - loss: 0.3952 - categorical_accuracy: 0.8589 - val_loss: 0.3607 - val_categorical_accuracy: 0.8668 - 872ms/epoch - 6ms/step
Epoch 25/250
141/141 - 1s - loss: 0.3882 - categorical_accuracy: 0.8614 - val_loss: 0.3441 - val_categorical_accuracy: 0.8733 - 875ms/epoch - 6ms/step
Epoch 26/250
141/141 - 1s - loss: 0.3577 - categorical_accuracy: 0.8699 - val_loss: 0.3440 - val_categorical_accuracy: 0.8750 - 877ms/epoch - 6ms/step
Epoch 27/250
141/141 - 1s - loss: 0.3659 - categorical_accuracy: 0.8692 - val_loss: 0.3453 - val_categorical_accuracy: 0.8746 - 861ms/epoch - 6ms/step
Epoch 28/250
141/141 - 1s - loss: 0.3682 - categorical_accuracy: 0.8701 - val_loss: 0.3656 - val_categorical_accuracy: 0.8675 - 861ms/epoch - 6ms/step
Epoch 29/250
141/141 - 1s - loss: 0.3323 - categorical_accuracy: 0.8797 - val_loss: 0.3306 - val_categorical_accuracy: 0.8807 - 1s/epoch - 7ms/step
Epoch 30/250
141/141 - 1s - loss: 0.3209 - categorical_accuracy: 0.8848 - val_loss: 0.3067 - val_categorical_accuracy: 0.8891 - 863ms/epoch - 6ms/step
Epoch 31/250
141/141 - 1s - loss: 0.3085 - categorical_accuracy: 0.8876 - val_loss: 0.3810 - val_categorical_accuracy: 0.8580 - 845ms/epoch - 6ms/step
Epoch 32/250
141/141 - 1s - loss: 0.2976 - categorical_accuracy: 0.8918 - val_loss: 0.2953 - val_categorical_accuracy: 0.8919 - 863ms/epoch - 6ms/step
Epoch 33/250
141/141 - 1s - loss: 0.4034 - categorical_accuracy: 0.8657 - val_loss: 0.3284 - val_categorical_accuracy: 0.8807 - 874ms/epoch - 6ms/step
Epoch 34/250
141/141 - 1s - loss: 0.3041 - categorical_accuracy: 0.8918 - val_loss: 0.3133 - val_categorical_accuracy: 0.8867 - 857ms/epoch - 6ms/step
Epoch 35/250
141/141 - 1s - loss: 0.2922 - categorical_accuracy: 0.8963 - val_loss: 0.2812 - val_categorical_accuracy: 0.8986 - 841ms/epoch - 6ms/step
Epoch 36/250
141/141 - 1s - loss: 0.2785 - categorical_accuracy: 0.9005 - val_loss: 0.2959 - val_categorical_accuracy: 0.8924 - 886ms/epoch - 6ms/step
Epoch 37/250
141/141 - 1s - loss: 0.2651 - categorical_accuracy: 0.9039 - val_loss: 0.4355 - val_categorical_accuracy: 0.8461 - 859ms/epoch - 6ms/step
Epoch 38/250
141/141 - 1s - loss: 0.2639 - categorical_accuracy: 0.9043 - val_loss: 0.4872 - val_categorical_accuracy: 0.8152 - 861ms/epoch - 6ms/step
Epoch 39/250
141/141 - 1s - loss: 0.3123 - categorical_accuracy: 0.8945 - val_loss: 1.0382 - val_categorical_accuracy: 0.6759 - 847ms/epoch - 6ms/step
Epoch 40/250
141/141 - 1s - loss: 0.2584 - categorical_accuracy: 0.9087 - val_loss: 0.2674 - val_categorical_accuracy: 0.9035 - 875ms/epoch - 6ms/step
Epoch 41/250
141/141 - 1s - loss: 0.2441 - categorical_accuracy: 0.9124 - val_loss: 0.2745 - val_categorical_accuracy: 0.9031 - 859ms/epoch - 6ms/step
Epoch 42/250
141/141 - 1s - loss: 0.3289 - categorical_accuracy: 0.8923 - val_loss: 0.2549 - val_categorical_accuracy: 0.9078 - 859ms/epoch - 6ms/step
Epoch 43/250
141/141 - 1s - loss: 0.2519 - categorical_accuracy: 0.9114 - val_loss: 0.5886 - val_categorical_accuracy: 0.8141 - 860ms/epoch - 6ms/step
Epoch 44/250
141/141 - 1s - loss: 0.2474 - categorical_accuracy: 0.9124 - val_loss: 0.2342 - val_categorical_accuracy: 0.9167 - 858ms/epoch - 6ms/step
Epoch 45/250
141/141 - 1s - loss: 0.2302 - categorical_accuracy: 0.9179 - val_loss: 0.2472 - val_categorical_accuracy: 0.9131 - 868ms/epoch - 6ms/step
Epoch 46/250
141/141 - 1s - loss: 0.2700 - categorical_accuracy: 0.9086 - val_loss: 0.2287 - val_categorical_accuracy: 0.9178 - 855ms/epoch - 6ms/step
Epoch 47/250
141/141 - 1s - loss: 0.2216 - categorical_accuracy: 0.9209 - val_loss: 0.2725 - val_categorical_accuracy: 0.9033 - 869ms/epoch - 6ms/step
Epoch 48/250
141/141 - 1s - loss: 0.2207 - categorical_accuracy: 0.9208 - val_loss: 0.2652 - val_categorical_accuracy: 0.9075 - 876ms/epoch - 6ms/step
Epoch 49/250
141/141 - 1s - loss: 0.2160 - categorical_accuracy: 0.9230 - val_loss: 0.3334 - val_categorical_accuracy: 0.8808 - 893ms/epoch - 6ms/step
Epoch 50/250
141/141 - 1s - loss: 0.2303 - categorical_accuracy: 0.9191 - val_loss: 0.2543 - val_categorical_accuracy: 0.9092 - 878ms/epoch - 6ms/step
Epoch 51/250
141/141 - 1s - loss: 0.2172 - categorical_accuracy: 0.9234 - val_loss: 0.2225 - val_categorical_accuracy: 0.9214 - 859ms/epoch - 6ms/step
Epoch 52/250
141/141 - 1s - loss: 0.2061 - categorical_accuracy: 0.9269 - val_loss: 0.2601 - val_categorical_accuracy: 0.9062 - 877ms/epoch - 6ms/step
Epoch 53/250
141/141 - 1s - loss: 0.2046 - categorical_accuracy: 0.9269 - val_loss: 0.2517 - val_categorical_accuracy: 0.9119 - 859ms/epoch - 6ms/step
Epoch 54/250
141/141 - 1s - loss: 0.2577 - categorical_accuracy: 0.9155 - val_loss: 0.2402 - val_categorical_accuracy: 0.9152 - 871ms/epoch - 6ms/step
Epoch 55/250
141/141 - 1s - loss: 0.2011 - categorical_accuracy: 0.9286 - val_loss: 0.2186 - val_categorical_accuracy: 0.9231 - 854ms/epoch - 6ms/step
Epoch 56/250
141/141 - 1s - loss: 0.1953 - categorical_accuracy: 0.9306 - val_loss: 0.3210 - val_categorical_accuracy: 0.8834 - 876ms/epoch - 6ms/step
Epoch 57/250
141/141 - 1s - loss: 0.1984 - categorical_accuracy: 0.9305 - val_loss: 0.2131 - val_categorical_accuracy: 0.9248 - 872ms/epoch - 6ms/step
Epoch 58/250
141/141 - 1s - loss: 0.4399 - categorical_accuracy: 0.8717 - val_loss: 0.3710 - val_categorical_accuracy: 0.8745 - 875ms/epoch - 6ms/step
Epoch 59/250
141/141 - 1s - loss: 0.2365 - categorical_accuracy: 0.9173 - val_loss: 0.2940 - val_categorical_accuracy: 0.8976 - 862ms/epoch - 6ms/step
Epoch 60/250
141/141 - 1s - loss: 0.1988 - categorical_accuracy: 0.9299 - val_loss: 0.2168 - val_categorical_accuracy: 0.9242 - 863ms/epoch - 6ms/step
Epoch 61/250
141/141 - 1s - loss: 0.1897 - categorical_accuracy: 0.9334 - val_loss: 0.3315 - val_categorical_accuracy: 0.8864 - 856ms/epoch - 6ms/step
Epoch 62/250
141/141 - 1s - loss: 0.1860 - categorical_accuracy: 0.9349 - val_loss: 0.2283 - val_categorical_accuracy: 0.9198 - 859ms/epoch - 6ms/step
Epoch 63/250
141/141 - 1s - loss: 0.1847 - categorical_accuracy: 0.9351 - val_loss: 0.2150 - val_categorical_accuracy: 0.9267 - 861ms/epoch - 6ms/step
Epoch 64/250
141/141 - 1s - loss: 0.1793 - categorical_accuracy: 0.9369 - val_loss: 0.2206 - val_categorical_accuracy: 0.9221 - 863ms/epoch - 6ms/step
Epoch 65/250
141/141 - 1s - loss: 0.1742 - categorical_accuracy: 0.9388 - val_loss: 0.2086 - val_categorical_accuracy: 0.9293 - 874ms/epoch - 6ms/step
Epoch 66/250
141/141 - 1s - loss: 0.3272 - categorical_accuracy: 0.9005 - val_loss: 0.2118 - val_categorical_accuracy: 0.9280 - 876ms/epoch - 6ms/step
Epoch 67/250
141/141 - 1s - loss: 0.1767 - categorical_accuracy: 0.9382 - val_loss: 0.1943 - val_categorical_accuracy: 0.9319 - 844ms/epoch - 6ms/step
Epoch 68/250
141/141 - 1s - loss: 0.1789 - categorical_accuracy: 0.9382 - val_loss: 0.1955 - val_categorical_accuracy: 0.9317 - 862ms/epoch - 6ms/step
Epoch 69/250
141/141 - 1s - loss: 0.1870 - categorical_accuracy: 0.9373 - val_loss: 0.2257 - val_categorical_accuracy: 0.9216 - 876ms/epoch - 6ms/step
Epoch 70/250
141/141 - 1s - loss: 0.1621 - categorical_accuracy: 0.9431 - val_loss: 0.2778 - val_categorical_accuracy: 0.8988 - 866ms/epoch - 6ms/step
Epoch 71/250
141/141 - 1s - loss: 0.1723 - categorical_accuracy: 0.9401 - val_loss: 0.1929 - val_categorical_accuracy: 0.9328 - 860ms/epoch - 6ms/step
Epoch 72/250
141/141 - 1s - loss: 0.1604 - categorical_accuracy: 0.9442 - val_loss: 0.1901 - val_categorical_accuracy: 0.9334 - 861ms/epoch - 6ms/step
Epoch 73/250
141/141 - 1s - loss: 0.1838 - categorical_accuracy: 0.9385 - val_loss: 0.1828 - val_categorical_accuracy: 0.9379 - 873ms/epoch - 6ms/step
Epoch 74/250
141/141 - 1s - loss: 0.1718 - categorical_accuracy: 0.9417 - val_loss: 0.3322 - val_categorical_accuracy: 0.8868 - 878ms/epoch - 6ms/step
Epoch 75/250
141/141 - 1s - loss: 0.1571 - categorical_accuracy: 0.9454 - val_loss: 0.2081 - val_categorical_accuracy: 0.9282 - 860ms/epoch - 6ms/step
Epoch 76/250
141/141 - 1s - loss: 0.1644 - categorical_accuracy: 0.9435 - val_loss: 0.1800 - val_categorical_accuracy: 0.9384 - 875ms/epoch - 6ms/step
Epoch 77/250
141/141 - 1s - loss: 0.1574 - categorical_accuracy: 0.9466 - val_loss: 0.2039 - val_categorical_accuracy: 0.9306 - 857ms/epoch - 6ms/step
Epoch 78/250
141/141 - 1s - loss: 0.1729 - categorical_accuracy: 0.9422 - val_loss: 0.1936 - val_categorical_accuracy: 0.9323 - 860ms/epoch - 6ms/step
Epoch 79/250
141/141 - 1s - loss: 0.1743 - categorical_accuracy: 0.9418 - val_loss: 0.1943 - val_categorical_accuracy: 0.9345 - 860ms/epoch - 6ms/step
Epoch 80/250
141/141 - 1s - loss: 0.1570 - categorical_accuracy: 0.9463 - val_loss: 0.2148 - val_categorical_accuracy: 0.9250 - 887ms/epoch - 6ms/step
Epoch 81/250
141/141 - 1s - loss: 0.1404 - categorical_accuracy: 0.9510 - val_loss: 0.1941 - val_categorical_accuracy: 0.9314 - 870ms/epoch - 6ms/step
Epoch 82/250
141/141 - 1s - loss: 0.1433 - categorical_accuracy: 0.9504 - val_loss: 0.1990 - val_categorical_accuracy: 0.9327 - 863ms/epoch - 6ms/step
Epoch 83/250
141/141 - 1s - loss: 0.1430 - categorical_accuracy: 0.9502 - val_loss: 0.1839 - val_categorical_accuracy: 0.9358 - 877ms/epoch - 6ms/step
Epoch 84/250
141/141 - 1s - loss: 0.2288 - categorical_accuracy: 0.9316 - val_loss: 0.1718 - val_categorical_accuracy: 0.9421 - 859ms/epoch - 6ms/step
Epoch 85/250
141/141 - 1s - loss: 0.1417 - categorical_accuracy: 0.9512 - val_loss: 0.2080 - val_categorical_accuracy: 0.9257 - 859ms/epoch - 6ms/step
Epoch 86/250
141/141 - 1s - loss: 0.1368 - categorical_accuracy: 0.9525 - val_loss: 0.1860 - val_categorical_accuracy: 0.9350 - 861ms/epoch - 6ms/step
Epoch 87/250
141/141 - 1s - loss: 0.1394 - categorical_accuracy: 0.9515 - val_loss: 0.1850 - val_categorical_accuracy: 0.9379 - 892ms/epoch - 6ms/step
Epoch 88/250
141/141 - 1s - loss: 0.1487 - categorical_accuracy: 0.9494 - val_loss: 0.2377 - val_categorical_accuracy: 0.9164 - 861ms/epoch - 6ms/step
Epoch 89/250
141/141 - 1s - loss: 0.1361 - categorical_accuracy: 0.9526 - val_loss: 0.1721 - val_categorical_accuracy: 0.9409 - 873ms/epoch - 6ms/step
Epoch 90/250
141/141 - 1s - loss: 0.1309 - categorical_accuracy: 0.9545 - val_loss: 0.2585 - val_categorical_accuracy: 0.9095 - 861ms/epoch - 6ms/step
Epoch 91/250
141/141 - 1s - loss: 0.1736 - categorical_accuracy: 0.9442 - val_loss: 0.1717 - val_categorical_accuracy: 0.9410 - 873ms/epoch - 6ms/step
Epoch 92/250
141/141 - 1s - loss: 0.1991 - categorical_accuracy: 0.9388 - val_loss: 0.1827 - val_categorical_accuracy: 0.9384 - 860ms/epoch - 6ms/step
Epoch 93/250
141/141 - 1s - loss: 0.1262 - categorical_accuracy: 0.9570 - val_loss: 0.1819 - val_categorical_accuracy: 0.9372 - 859ms/epoch - 6ms/step
Epoch 94/250
141/141 - 1s - loss: 0.1280 - categorical_accuracy: 0.9561 - val_loss: 0.2215 - val_categorical_accuracy: 0.9228 - 874ms/epoch - 6ms/step
Epoch 95/250
141/141 - 1s - loss: 0.1286 - categorical_accuracy: 0.9556 - val_loss: 0.3622 - val_categorical_accuracy: 0.8899 - 861ms/epoch - 6ms/step
Epoch 96/250
141/141 - 1s - loss: 0.1286 - categorical_accuracy: 0.9557 - val_loss: 0.1804 - val_categorical_accuracy: 0.9373 - 877ms/epoch - 6ms/step
Epoch 97/250
141/141 - 1s - loss: 0.1468 - categorical_accuracy: 0.9515 - val_loss: 0.1809 - val_categorical_accuracy: 0.9382 - 878ms/epoch - 6ms/step
Epoch 98/250
141/141 - 1s - loss: 0.1325 - categorical_accuracy: 0.9552 - val_loss: 0.1651 - val_categorical_accuracy: 0.9456 - 889ms/epoch - 6ms/step
Epoch 99/250
141/141 - 1s - loss: 0.1221 - categorical_accuracy: 0.9581 - val_loss: 0.1982 - val_categorical_accuracy: 0.9346 - 862ms/epoch - 6ms/step
Epoch 100/250
141/141 - 1s - loss: 0.1316 - categorical_accuracy: 0.9545 - val_loss: 0.1576 - val_categorical_accuracy: 0.9467 - 843ms/epoch - 6ms/step
Epoch 101/250
141/141 - 1s - loss: 0.1210 - categorical_accuracy: 0.9577 - val_loss: 0.1810 - val_categorical_accuracy: 0.9396 - 872ms/epoch - 6ms/step
Epoch 102/250
141/141 - 1s - loss: 0.1666 - categorical_accuracy: 0.9479 - val_loss: 0.2874 - val_categorical_accuracy: 0.9026 - 875ms/epoch - 6ms/step
Epoch 103/250
141/141 - 1s - loss: 0.1198 - categorical_accuracy: 0.9588 - val_loss: 0.1618 - val_categorical_accuracy: 0.9460 - 861ms/epoch - 6ms/step
Epoch 104/250
141/141 - 1s - loss: 0.1233 - categorical_accuracy: 0.9571 - val_loss: 0.1945 - val_categorical_accuracy: 0.9313 - 860ms/epoch - 6ms/step
Epoch 105/250
141/141 - 1s - loss: 0.1131 - categorical_accuracy: 0.9610 - val_loss: 0.1843 - val_categorical_accuracy: 0.9365 - 876ms/epoch - 6ms/step
Epoch 106/250
141/141 - 1s - loss: 0.1641 - categorical_accuracy: 0.9479 - val_loss: 0.1675 - val_categorical_accuracy: 0.9441 - 873ms/epoch - 6ms/step
Epoch 107/250
141/141 - 1s - loss: 0.1154 - categorical_accuracy: 0.9608 - val_loss: 0.1999 - val_categorical_accuracy: 0.9311 - 862ms/epoch - 6ms/step
Epoch 108/250
141/141 - 1s - loss: 0.1187 - categorical_accuracy: 0.9594 - val_loss: 0.1675 - val_categorical_accuracy: 0.9448 - 874ms/epoch - 6ms/step
Epoch 109/250
141/141 - 1s - loss: 0.1309 - categorical_accuracy: 0.9575 - val_loss: 0.1760 - val_categorical_accuracy: 0.9410 - 878ms/epoch - 6ms/step
Epoch 110/250
141/141 - 1s - loss: 0.1619 - categorical_accuracy: 0.9492 - val_loss: 0.1615 - val_categorical_accuracy: 0.9462 - 863ms/epoch - 6ms/step
Epoch 111/250
141/141 - 1s - loss: 0.1040 - categorical_accuracy: 0.9646 - val_loss: 0.2069 - val_categorical_accuracy: 0.9344 - 859ms/epoch - 6ms/step
Epoch 112/250
141/141 - 1s - loss: 0.1190 - categorical_accuracy: 0.9593 - val_loss: 0.2418 - val_categorical_accuracy: 0.9179 - 875ms/epoch - 6ms/step
Epoch 113/250
141/141 - 1s - loss: 0.1105 - categorical_accuracy: 0.9620 - val_loss: 0.1855 - val_categorical_accuracy: 0.9412 - 859ms/epoch - 6ms/step
Epoch 114/250
141/141 - 1s - loss: 0.1099 - categorical_accuracy: 0.9625 - val_loss: 0.2668 - val_categorical_accuracy: 0.9067 - 861ms/epoch - 6ms/step
Epoch 115/250
141/141 - 1s - loss: 0.1245 - categorical_accuracy: 0.9583 - val_loss: 0.1596 - val_categorical_accuracy: 0.9465 - 873ms/epoch - 6ms/step
Epoch 116/250
141/141 - 1s - loss: 0.1000 - categorical_accuracy: 0.9660 - val_loss: 0.1743 - val_categorical_accuracy: 0.9430 - 877ms/epoch - 6ms/step
Epoch 117/250
141/141 - 1s - loss: 0.1326 - categorical_accuracy: 0.9559 - val_loss: 0.1682 - val_categorical_accuracy: 0.9447 - 894ms/epoch - 6ms/step
Epoch 118/250
141/141 - 1s - loss: 0.1069 - categorical_accuracy: 0.9631 - val_loss: 0.1737 - val_categorical_accuracy: 0.9425 - 909ms/epoch - 6ms/step
Epoch 119/250
141/141 - 1s - loss: 0.1131 - categorical_accuracy: 0.9617 - val_loss: 0.1621 - val_categorical_accuracy: 0.9475 - 892ms/epoch - 6ms/step
Epoch 120/250
141/141 - 1s - loss: 0.1188 - categorical_accuracy: 0.9608 - val_loss: 0.1628 - val_categorical_accuracy: 0.9461 - 859ms/epoch - 6ms/step
Epoch 121/250
141/141 - 1s - loss: 0.1056 - categorical_accuracy: 0.9638 - val_loss: 0.1527 - val_categorical_accuracy: 0.9503 - 861ms/epoch - 6ms/step
Epoch 122/250
141/141 - 1s - loss: 0.1152 - categorical_accuracy: 0.9609 - val_loss: 0.1602 - val_categorical_accuracy: 0.9471 - 861ms/epoch - 6ms/step
Epoch 123/250
141/141 - 1s - loss: 0.1051 - categorical_accuracy: 0.9644 - val_loss: 0.1623 - val_categorical_accuracy: 0.9488 - 868ms/epoch - 6ms/step
Epoch 124/250
141/141 - 1s - loss: 0.1056 - categorical_accuracy: 0.9636 - val_loss: 0.1577 - val_categorical_accuracy: 0.9498 - 859ms/epoch - 6ms/step
Epoch 125/250
141/141 - 1s - loss: 0.1479 - categorical_accuracy: 0.9530 - val_loss: 0.1548 - val_categorical_accuracy: 0.9491 - 859ms/epoch - 6ms/step
Epoch 126/250
141/141 - 1s - loss: 0.3767 - categorical_accuracy: 0.8948 - val_loss: 0.4585 - val_categorical_accuracy: 0.8434 - 860ms/epoch - 6ms/step
Epoch 127/250
141/141 - 1s - loss: 0.1575 - categorical_accuracy: 0.9466 - val_loss: 0.1600 - val_categorical_accuracy: 0.9477 - 877ms/epoch - 6ms/step
Epoch 128/250
141/141 - 1s - loss: 0.1096 - categorical_accuracy: 0.9624 - val_loss: 0.1704 - val_categorical_accuracy: 0.9450 - 859ms/epoch - 6ms/step
Epoch 129/250
141/141 - 1s - loss: 0.1005 - categorical_accuracy: 0.9660 - val_loss: 0.1630 - val_categorical_accuracy: 0.9459 - 872ms/epoch - 6ms/step
Epoch 130/250
141/141 - 1s - loss: 0.1045 - categorical_accuracy: 0.9641 - val_loss: 0.1596 - val_categorical_accuracy: 0.9489 - 875ms/epoch - 6ms/step
Epoch 131/250
141/141 - 1s - loss: 0.1088 - categorical_accuracy: 0.9633 - val_loss: 0.1568 - val_categorical_accuracy: 0.9504 - 861ms/epoch - 6ms/step
Epoch 132/250
141/141 - 1s - loss: 0.1073 - categorical_accuracy: 0.9644 - val_loss: 0.9410 - val_categorical_accuracy: 0.7910 - 862ms/epoch - 6ms/step
Epoch 133/250
141/141 - 1s - loss: 0.1063 - categorical_accuracy: 0.9649 - val_loss: 0.1712 - val_categorical_accuracy: 0.9447 - 857ms/epoch - 6ms/step
Epoch 134/250
141/141 - 1s - loss: 0.1173 - categorical_accuracy: 0.9621 - val_loss: 0.1554 - val_categorical_accuracy: 0.9502 - 873ms/epoch - 6ms/step
Epoch 135/250
141/141 - 1s - loss: 0.0960 - categorical_accuracy: 0.9671 - val_loss: 0.1652 - val_categorical_accuracy: 0.9450 - 859ms/epoch - 6ms/step
Epoch 136/250
141/141 - 1s - loss: 0.0955 - categorical_accuracy: 0.9670 - val_loss: 0.1862 - val_categorical_accuracy: 0.9371 - 845ms/epoch - 6ms/step
Epoch 137/250
141/141 - 1s - loss: 0.1141 - categorical_accuracy: 0.9623 - val_loss: 0.1593 - val_categorical_accuracy: 0.9470 - 876ms/epoch - 6ms/step
Epoch 138/250
141/141 - 1s - loss: 0.0916 - categorical_accuracy: 0.9689 - val_loss: 0.1471 - val_categorical_accuracy: 0.9528 - 869ms/epoch - 6ms/step
Epoch 139/250
141/141 - 1s - loss: 0.0949 - categorical_accuracy: 0.9675 - val_loss: 0.1534 - val_categorical_accuracy: 0.9490 - 859ms/epoch - 6ms/step
Epoch 140/250
141/141 - 1s - loss: 0.1346 - categorical_accuracy: 0.9577 - val_loss: 0.1524 - val_categorical_accuracy: 0.9494 - 861ms/epoch - 6ms/step
Epoch 141/250
141/141 - 1s - loss: 0.0889 - categorical_accuracy: 0.9700 - val_loss: 0.1452 - val_categorical_accuracy: 0.9539 - 876ms/epoch - 6ms/step
Epoch 142/250
141/141 - 1s - loss: 0.0974 - categorical_accuracy: 0.9664 - val_loss: 0.1627 - val_categorical_accuracy: 0.9500 - 876ms/epoch - 6ms/step
Epoch 143/250
141/141 - 1s - loss: 0.0920 - categorical_accuracy: 0.9687 - val_loss: 0.1695 - val_categorical_accuracy: 0.9471 - 862ms/epoch - 6ms/step
Epoch 144/250
141/141 - 1s - loss: 0.1698 - categorical_accuracy: 0.9498 - val_loss: 0.1746 - val_categorical_accuracy: 0.9423 - 844ms/epoch - 6ms/step
Epoch 145/250
141/141 - 1s - loss: 0.1049 - categorical_accuracy: 0.9654 - val_loss: 0.1478 - val_categorical_accuracy: 0.9530 - 891ms/epoch - 6ms/step
Epoch 146/250
141/141 - 1s - loss: 0.1210 - categorical_accuracy: 0.9619 - val_loss: 0.1598 - val_categorical_accuracy: 0.9499 - 873ms/epoch - 6ms/step
Epoch 147/250
141/141 - 1s - loss: 0.0882 - categorical_accuracy: 0.9700 - val_loss: 0.1704 - val_categorical_accuracy: 0.9437 - 869ms/epoch - 6ms/step
Epoch 148/250
141/141 - 1s - loss: 0.0838 - categorical_accuracy: 0.9718 - val_loss: 0.1538 - val_categorical_accuracy: 0.9531 - 853ms/epoch - 6ms/step
Epoch 149/250
141/141 - 1s - loss: 0.0898 - categorical_accuracy: 0.9691 - val_loss: 0.1552 - val_categorical_accuracy: 0.9522 - 858ms/epoch - 6ms/step
Epoch 150/250
141/141 - 1s - loss: 0.0881 - categorical_accuracy: 0.9698 - val_loss: 0.2758 - val_categorical_accuracy: 0.9190 - 877ms/epoch - 6ms/step
Epoch 151/250
141/141 - 1s - loss: 0.0925 - categorical_accuracy: 0.9683 - val_loss: 0.1576 - val_categorical_accuracy: 0.9503 - 874ms/epoch - 6ms/step
Epoch 152/250
141/141 - 1s - loss: 0.0862 - categorical_accuracy: 0.9704 - val_loss: 0.1600 - val_categorical_accuracy: 0.9487 - 874ms/epoch - 6ms/step
Epoch 153/250
141/141 - 1s - loss: 0.1306 - categorical_accuracy: 0.9601 - val_loss: 0.1745 - val_categorical_accuracy: 0.9426 - 859ms/epoch - 6ms/step
Epoch 154/250
141/141 - 1s - loss: 0.0837 - categorical_accuracy: 0.9718 - val_loss: 0.1418 - val_categorical_accuracy: 0.9561 - 857ms/epoch - 6ms/step
Epoch 155/250
141/141 - 1s - loss: 0.0840 - categorical_accuracy: 0.9716 - val_loss: 0.1575 - val_categorical_accuracy: 0.9502 - 872ms/epoch - 6ms/step
Epoch 156/250
141/141 - 1s - loss: 0.2027 - categorical_accuracy: 0.9387 - val_loss: 0.1551 - val_categorical_accuracy: 0.9503 - 875ms/epoch - 6ms/step
Epoch 157/250
141/141 - 1s - loss: 0.0899 - categorical_accuracy: 0.9693 - val_loss: 0.1662 - val_categorical_accuracy: 0.9470 - 860ms/epoch - 6ms/step
Epoch 158/250
141/141 - 1s - loss: 0.0821 - categorical_accuracy: 0.9720 - val_loss: 0.1502 - val_categorical_accuracy: 0.9543 - 854ms/epoch - 6ms/step
Epoch 159/250
141/141 - 1s - loss: 0.0872 - categorical_accuracy: 0.9702 - val_loss: 0.1792 - val_categorical_accuracy: 0.9441 - 858ms/epoch - 6ms/step
Epoch 160/250
141/141 - 1s - loss: 0.0927 - categorical_accuracy: 0.9689 - val_loss: 0.1789 - val_categorical_accuracy: 0.9448 - 857ms/epoch - 6ms/step
Epoch 161/250
141/141 - 1s - loss: 0.0833 - categorical_accuracy: 0.9715 - val_loss: 0.1609 - val_categorical_accuracy: 0.9510 - 860ms/epoch - 6ms/step
Epoch 162/250
141/141 - 1s - loss: 0.0880 - categorical_accuracy: 0.9700 - val_loss: 0.1691 - val_categorical_accuracy: 0.9483 - 860ms/epoch - 6ms/step
Epoch 163/250
141/141 - 1s - loss: 0.0990 - categorical_accuracy: 0.9684 - val_loss: 0.7348 - val_categorical_accuracy: 0.8050 - 876ms/epoch - 6ms/step
Epoch 164/250
141/141 - 1s - loss: 0.0933 - categorical_accuracy: 0.9688 - val_loss: 0.1458 - val_categorical_accuracy: 0.9552 - 863ms/epoch - 6ms/step
Epoch 165/250
141/141 - 1s - loss: 0.0805 - categorical_accuracy: 0.9725 - val_loss: 0.2152 - val_categorical_accuracy: 0.9363 - 861ms/epoch - 6ms/step
Epoch 166/250
141/141 - 1s - loss: 0.0901 - categorical_accuracy: 0.9692 - val_loss: 0.1484 - val_categorical_accuracy: 0.9528 - 871ms/epoch - 6ms/step
Epoch 167/250
141/141 - 1s - loss: 0.0814 - categorical_accuracy: 0.9722 - val_loss: 0.1956 - val_categorical_accuracy: 0.9409 - 879ms/epoch - 6ms/step
Epoch 168/250
141/141 - 1s - loss: 0.1113 - categorical_accuracy: 0.9650 - val_loss: 0.2209 - val_categorical_accuracy: 0.9339 - 845ms/epoch - 6ms/step
Epoch 169/250
141/141 - 1s - loss: 0.0866 - categorical_accuracy: 0.9705 - val_loss: 0.1465 - val_categorical_accuracy: 0.9558 - 861ms/epoch - 6ms/step
Epoch 170/250
141/141 - 1s - loss: 0.0881 - categorical_accuracy: 0.9699 - val_loss: 0.2100 - val_categorical_accuracy: 0.9331 - 979ms/epoch - 7ms/step
Epoch 171/250
141/141 - 1s - loss: 0.0767 - categorical_accuracy: 0.9737 - val_loss: 0.1576 - val_categorical_accuracy: 0.9522 - 882ms/epoch - 6ms/step
Epoch 172/250
141/141 - 1s - loss: 0.1004 - categorical_accuracy: 0.9676 - val_loss: 0.3023 - val_categorical_accuracy: 0.9002 - 868ms/epoch - 6ms/step
Epoch 173/250
141/141 - 1s - loss: 0.0825 - categorical_accuracy: 0.9717 - val_loss: 0.1551 - val_categorical_accuracy: 0.9516 - 883ms/epoch - 6ms/step
Epoch 174/250
141/141 - 1s - loss: 0.0778 - categorical_accuracy: 0.9733 - val_loss: 0.1693 - val_categorical_accuracy: 0.9485 - 882ms/epoch - 6ms/step
Epoch 175/250
141/141 - 1s - loss: 0.0839 - categorical_accuracy: 0.9714 - val_loss: 0.1494 - val_categorical_accuracy: 0.9549 - 871ms/epoch - 6ms/step
Epoch 176/250
141/141 - 1s - loss: 0.1216 - categorical_accuracy: 0.9621 - val_loss: 0.1550 - val_categorical_accuracy: 0.9505 - 868ms/epoch - 6ms/step
Epoch 177/250
141/141 - 1s - loss: 0.0746 - categorical_accuracy: 0.9748 - val_loss: 0.1573 - val_categorical_accuracy: 0.9503 - 860ms/epoch - 6ms/step
Epoch 178/250
141/141 - 1s - loss: 0.0997 - categorical_accuracy: 0.9668 - val_loss: 0.1502 - val_categorical_accuracy: 0.9538 - 860ms/epoch - 6ms/step
Epoch 179/250
141/141 - 1s - loss: 0.0752 - categorical_accuracy: 0.9743 - val_loss: 0.1609 - val_categorical_accuracy: 0.9520 - 860ms/epoch - 6ms/step
Epoch 180/250
141/141 - 1s - loss: 0.0735 - categorical_accuracy: 0.9748 - val_loss: 0.2347 - val_categorical_accuracy: 0.9208 - 870ms/epoch - 6ms/step
Epoch 181/250
141/141 - 1s - loss: 0.1234 - categorical_accuracy: 0.9630 - val_loss: 0.1552 - val_categorical_accuracy: 0.9523 - 880ms/epoch - 6ms/step
Epoch 182/250
141/141 - 1s - loss: 0.0785 - categorical_accuracy: 0.9728 - val_loss: 0.1443 - val_categorical_accuracy: 0.9567 - 870ms/epoch - 6ms/step
Epoch 183/250
141/141 - 1s - loss: 0.0799 - categorical_accuracy: 0.9727 - val_loss: 0.1822 - val_categorical_accuracy: 0.9438 - 860ms/epoch - 6ms/step
Epoch 184/250
141/141 - 1s - loss: 0.0769 - categorical_accuracy: 0.9736 - val_loss: 0.4298 - val_categorical_accuracy: 0.8844 - 870ms/epoch - 6ms/step
Epoch 185/250
141/141 - 1s - loss: 0.1223 - categorical_accuracy: 0.9637 - val_loss: 0.1655 - val_categorical_accuracy: 0.9498 - 890ms/epoch - 6ms/step
Epoch 186/250
141/141 - 1s - loss: 0.0740 - categorical_accuracy: 0.9750 - val_loss: 0.1451 - val_categorical_accuracy: 0.9564 - 870ms/epoch - 6ms/step
Epoch 187/250
141/141 - 1s - loss: 0.0766 - categorical_accuracy: 0.9737 - val_loss: 0.1867 - val_categorical_accuracy: 0.9462 - 860ms/epoch - 6ms/step
Epoch 188/250
141/141 - 1s - loss: 0.0754 - categorical_accuracy: 0.9744 - val_loss: 0.2563 - val_categorical_accuracy: 0.9247 - 880ms/epoch - 6ms/step
Epoch 189/250
141/141 - 1s - loss: 0.0780 - categorical_accuracy: 0.9733 - val_loss: 0.1822 - val_categorical_accuracy: 0.9473 - 880ms/epoch - 6ms/step
Epoch 190/250
141/141 - 1s - loss: 0.0907 - categorical_accuracy: 0.9705 - val_loss: 1.5530 - val_categorical_accuracy: 0.7188 - 860ms/epoch - 6ms/step
Epoch 191/250
141/141 - 1s - loss: 0.1122 - categorical_accuracy: 0.9655 - val_loss: 0.1439 - val_categorical_accuracy: 0.9578 - 860ms/epoch - 6ms/step
Epoch 192/250
141/141 - 1s - loss: 0.0722 - categorical_accuracy: 0.9754 - val_loss: 0.1476 - val_categorical_accuracy: 0.9549 - 860ms/epoch - 6ms/step
Epoch 193/250
141/141 - 1s - loss: 0.0983 - categorical_accuracy: 0.9687 - val_loss: 0.1546 - val_categorical_accuracy: 0.9538 - 850ms/epoch - 6ms/step
Epoch 194/250
141/141 - 1s - loss: 0.0703 - categorical_accuracy: 0.9758 - val_loss: 0.1588 - val_categorical_accuracy: 0.9527 - 850ms/epoch - 6ms/step
Epoch 195/250
141/141 - 1s - loss: 0.0696 - categorical_accuracy: 0.9763 - val_loss: 0.1485 - val_categorical_accuracy: 0.9574 - 860ms/epoch - 6ms/step
Epoch 196/250
141/141 - 1s - loss: 0.1343 - categorical_accuracy: 0.9606 - val_loss: 0.1452 - val_categorical_accuracy: 0.9563 - 860ms/epoch - 6ms/step
Epoch 197/250
141/141 - 1s - loss: 0.0694 - categorical_accuracy: 0.9764 - val_loss: 0.1692 - val_categorical_accuracy: 0.9500 - 870ms/epoch - 6ms/step
Epoch 198/250
141/141 - 1s - loss: 0.0717 - categorical_accuracy: 0.9755 - val_loss: 0.1505 - val_categorical_accuracy: 0.9559 - 870ms/epoch - 6ms/step
Epoch 199/250
141/141 - 1s - loss: 0.2541 - categorical_accuracy: 0.9296 - val_loss: 0.7448 - val_categorical_accuracy: 0.7460 - 870ms/epoch - 6ms/step
Epoch 200/250
141/141 - 1s - loss: 0.1760 - categorical_accuracy: 0.9395 - val_loss: 0.1804 - val_categorical_accuracy: 0.9432 - 860ms/epoch - 6ms/step
Epoch 201/250
141/141 - 1s - loss: 0.0831 - categorical_accuracy: 0.9717 - val_loss: 0.1549 - val_categorical_accuracy: 0.9520 - 860ms/epoch - 6ms/step
Epoch 202/250
141/141 - 1s - loss: 0.0765 - categorical_accuracy: 0.9739 - val_loss: 0.1601 - val_categorical_accuracy: 0.9497 - 860ms/epoch - 6ms/step
Epoch 203/250
141/141 - 1s - loss: 0.0767 - categorical_accuracy: 0.9736 - val_loss: 0.1492 - val_categorical_accuracy: 0.9534 - 860ms/epoch - 6ms/step
Epoch 204/250
141/141 - 1s - loss: 0.0748 - categorical_accuracy: 0.9745 - val_loss: 0.1655 - val_categorical_accuracy: 0.9464 - 860ms/epoch - 6ms/step
Epoch 205/250
141/141 - 1s - loss: 0.0713 - categorical_accuracy: 0.9758 - val_loss: 0.1524 - val_categorical_accuracy: 0.9559 - 860ms/epoch - 6ms/step
Epoch 206/250
141/141 - 1s - loss: 0.0772 - categorical_accuracy: 0.9737 - val_loss: 0.1527 - val_categorical_accuracy: 0.9549 - 860ms/epoch - 6ms/step
Epoch 207/250
141/141 - 1s - loss: 0.0769 - categorical_accuracy: 0.9739 - val_loss: 0.1616 - val_categorical_accuracy: 0.9517 - 1s/epoch - 7ms/step
Epoch 208/250
141/141 - 1s - loss: 0.0725 - categorical_accuracy: 0.9751 - val_loss: 0.1748 - val_categorical_accuracy: 0.9473 - 860ms/epoch - 6ms/step
Epoch 209/250
141/141 - 1s - loss: 0.0732 - categorical_accuracy: 0.9748 - val_loss: 0.1670 - val_categorical_accuracy: 0.9516 - 860ms/epoch - 6ms/step
Epoch 210/250
141/141 - 1s - loss: 0.0803 - categorical_accuracy: 0.9727 - val_loss: 0.1732 - val_categorical_accuracy: 0.9509 - 870ms/epoch - 6ms/step
Epoch 211/250
141/141 - 1s - loss: 0.0691 - categorical_accuracy: 0.9763 - val_loss: 0.1631 - val_categorical_accuracy: 0.9527 - 870ms/epoch - 6ms/step
Epoch 212/250
141/141 - 1s - loss: 0.1048 - categorical_accuracy: 0.9671 - val_loss: 0.1607 - val_categorical_accuracy: 0.9509 - 870ms/epoch - 6ms/step
Epoch 213/250
141/141 - 1s - loss: 0.0667 - categorical_accuracy: 0.9773 - val_loss: 0.1585 - val_categorical_accuracy: 0.9528 - 850ms/epoch - 6ms/step
Epoch 214/250
141/141 - 1s - loss: 0.0772 - categorical_accuracy: 0.9734 - val_loss: 0.1576 - val_categorical_accuracy: 0.9513 - 850ms/epoch - 6ms/step
Epoch 215/250
141/141 - 1s - loss: 0.1208 - categorical_accuracy: 0.9636 - val_loss: 0.1613 - val_categorical_accuracy: 0.9504 - 870ms/epoch - 6ms/step
Epoch 216/250
141/141 - 1s - loss: 0.0677 - categorical_accuracy: 0.9768 - val_loss: 0.1456 - val_categorical_accuracy: 0.9564 - 870ms/epoch - 6ms/step
Epoch 217/250
141/141 - 1s - loss: 0.0842 - categorical_accuracy: 0.9721 - val_loss: 0.1628 - val_categorical_accuracy: 0.9540 - 870ms/epoch - 6ms/step
Epoch 218/250
141/141 - 1s - loss: 0.0666 - categorical_accuracy: 0.9773 - val_loss: 0.1532 - val_categorical_accuracy: 0.9546 - 860ms/epoch - 6ms/step
Epoch 219/250
141/141 - 1s - loss: 0.0657 - categorical_accuracy: 0.9776 - val_loss: 0.1583 - val_categorical_accuracy: 0.9523 - 870ms/epoch - 6ms/step
Epoch 220/250
141/141 - 1s - loss: 0.1075 - categorical_accuracy: 0.9676 - val_loss: 0.1593 - val_categorical_accuracy: 0.9534 - 870ms/epoch - 6ms/step
Epoch 221/250
141/141 - 1s - loss: 0.0640 - categorical_accuracy: 0.9782 - val_loss: 0.1501 - val_categorical_accuracy: 0.9553 - 860ms/epoch - 6ms/step
Epoch 222/250
141/141 - 1s - loss: 0.0658 - categorical_accuracy: 0.9775 - val_loss: 0.1590 - val_categorical_accuracy: 0.9537 - 860ms/epoch - 6ms/step
Epoch 223/250
141/141 - 1s - loss: 0.0688 - categorical_accuracy: 0.9764 - val_loss: 0.1446 - val_categorical_accuracy: 0.9569 - 860ms/epoch - 6ms/step
Epoch 224/250
141/141 - 1s - loss: 0.0759 - categorical_accuracy: 0.9739 - val_loss: 0.1489 - val_categorical_accuracy: 0.9574 - 870ms/epoch - 6ms/step
Epoch 225/250
141/141 - 1s - loss: 0.0638 - categorical_accuracy: 0.9781 - val_loss: 0.1465 - val_categorical_accuracy: 0.9564 - 870ms/epoch - 6ms/step
Epoch 226/250
141/141 - 1s - loss: 0.0679 - categorical_accuracy: 0.9764 - val_loss: 0.1611 - val_categorical_accuracy: 0.9529 - 860ms/epoch - 6ms/step
Epoch 227/250
141/141 - 1s - loss: 0.0865 - categorical_accuracy: 0.9711 - val_loss: 0.2001 - val_categorical_accuracy: 0.9374 - 870ms/epoch - 6ms/step
Epoch 228/250
141/141 - 1s - loss: 0.0683 - categorical_accuracy: 0.9765 - val_loss: 0.1594 - val_categorical_accuracy: 0.9554 - 860ms/epoch - 6ms/step
Epoch 229/250
141/141 - 1s - loss: 0.0645 - categorical_accuracy: 0.9778 - val_loss: 0.1712 - val_categorical_accuracy: 0.9533 - 860ms/epoch - 6ms/step
Epoch 230/250
141/141 - 1s - loss: 0.0976 - categorical_accuracy: 0.9699 - val_loss: 0.1617 - val_categorical_accuracy: 0.9488 - 860ms/epoch - 6ms/step
Epoch 231/250
141/141 - 1s - loss: 0.0641 - categorical_accuracy: 0.9780 - val_loss: 0.1493 - val_categorical_accuracy: 0.9549 - 870ms/epoch - 6ms/step
Epoch 232/250
141/141 - 1s - loss: 0.0662 - categorical_accuracy: 0.9776 - val_loss: 0.1530 - val_categorical_accuracy: 0.9568 - 870ms/epoch - 6ms/step
Epoch 233/250
141/141 - 1s - loss: 0.0665 - categorical_accuracy: 0.9772 - val_loss: 0.1900 - val_categorical_accuracy: 0.9408 - 870ms/epoch - 6ms/step
Epoch 234/250
141/141 - 1s - loss: 0.0629 - categorical_accuracy: 0.9786 - val_loss: 0.1808 - val_categorical_accuracy: 0.9492 - 860ms/epoch - 6ms/step
Epoch 235/250
141/141 - 1s - loss: 0.0780 - categorical_accuracy: 0.9740 - val_loss: 0.1496 - val_categorical_accuracy: 0.9555 - 870ms/epoch - 6ms/step
Epoch 236/250
141/141 - 1s - loss: 0.0701 - categorical_accuracy: 0.9758 - val_loss: 0.1606 - val_categorical_accuracy: 0.9549 - 860ms/epoch - 6ms/step
Epoch 237/250
141/141 - 1s - loss: 0.0624 - categorical_accuracy: 0.9783 - val_loss: 0.1624 - val_categorical_accuracy: 0.9532 - 870ms/epoch - 6ms/step
Epoch 238/250
141/141 - 1s - loss: 0.0636 - categorical_accuracy: 0.9777 - val_loss: 0.1601 - val_categorical_accuracy: 0.9543 - 860ms/epoch - 6ms/step
Epoch 239/250
141/141 - 1s - loss: 0.0607 - categorical_accuracy: 0.9793 - val_loss: 0.1469 - val_categorical_accuracy: 0.9604 - 880ms/epoch - 6ms/step
Epoch 240/250
141/141 - 1s - loss: 0.0613 - categorical_accuracy: 0.9789 - val_loss: 0.1532 - val_categorical_accuracy: 0.9576 - 870ms/epoch - 6ms/step
Epoch 241/250
141/141 - 1s - loss: 0.1790 - categorical_accuracy: 0.9502 - val_loss: 0.1862 - val_categorical_accuracy: 0.9403 - 870ms/epoch - 6ms/step
Epoch 242/250
141/141 - 1s - loss: 0.0749 - categorical_accuracy: 0.9748 - val_loss: 0.1897 - val_categorical_accuracy: 0.9486 - 880ms/epoch - 6ms/step
Epoch 243/250
141/141 - 1s - loss: 0.0661 - categorical_accuracy: 0.9772 - val_loss: 0.1502 - val_categorical_accuracy: 0.9558 - 860ms/epoch - 6ms/step
Epoch 244/250
141/141 - 1s - loss: 0.0626 - categorical_accuracy: 0.9786 - val_loss: 0.2738 - val_categorical_accuracy: 0.9309 - 860ms/epoch - 6ms/step
Epoch 245/250
141/141 - 1s - loss: 0.1493 - categorical_accuracy: 0.9569 - val_loss: 0.1515 - val_categorical_accuracy: 0.9556 - 870ms/epoch - 6ms/step
Epoch 246/250
141/141 - 1s - loss: 0.0614 - categorical_accuracy: 0.9791 - val_loss: 0.1481 - val_categorical_accuracy: 0.9574 - 870ms/epoch - 6ms/step
Epoch 247/250
141/141 - 1s - loss: 0.0605 - categorical_accuracy: 0.9793 - val_loss: 0.1507 - val_categorical_accuracy: 0.9566 - 860ms/epoch - 6ms/step
Epoch 248/250
141/141 - 1s - loss: 0.0602 - categorical_accuracy: 0.9793 - val_loss: 0.1556 - val_categorical_accuracy: 0.9562 - 860ms/epoch - 6ms/step
Epoch 249/250
141/141 - 1s - loss: 0.0918 - categorical_accuracy: 0.9707 - val_loss: 0.1503 - val_categorical_accuracy: 0.9570 - 860ms/epoch - 6ms/step
Epoch 250/250
141/141 - 1s - loss: 0.0598 - categorical_accuracy: 0.9798 - val_loss: 0.1488 - val_categorical_accuracy: 0.9575 - 870ms/epoch - 6ms/step
processing fold # 7 
Epoch 1/250
141/141 - 2s - loss: 1.9031 - categorical_accuracy: 0.2879 - val_loss: 1.6151 - val_categorical_accuracy: 0.3932 - 2s/epoch - 12ms/step
Epoch 2/250
141/141 - 1s - loss: 1.5200 - categorical_accuracy: 0.4242 - val_loss: 1.2793 - val_categorical_accuracy: 0.5201 - 860ms/epoch - 6ms/step
Epoch 3/250
141/141 - 1s - loss: 1.3104 - categorical_accuracy: 0.5061 - val_loss: 1.1495 - val_categorical_accuracy: 0.5724 - 860ms/epoch - 6ms/step
Epoch 4/250
141/141 - 1s - loss: 1.1732 - categorical_accuracy: 0.5626 - val_loss: 1.0035 - val_categorical_accuracy: 0.6260 - 853ms/epoch - 6ms/step
Epoch 5/250
141/141 - 1s - loss: 1.0389 - categorical_accuracy: 0.6138 - val_loss: 1.0124 - val_categorical_accuracy: 0.6157 - 850ms/epoch - 6ms/step
Epoch 6/250
141/141 - 1s - loss: 0.9157 - categorical_accuracy: 0.6584 - val_loss: 0.7947 - val_categorical_accuracy: 0.7048 - 850ms/epoch - 6ms/step
Epoch 7/250
141/141 - 1s - loss: 0.8843 - categorical_accuracy: 0.6746 - val_loss: 0.8919 - val_categorical_accuracy: 0.6966 - 860ms/epoch - 6ms/step
Epoch 8/250
141/141 - 1s - loss: 0.8528 - categorical_accuracy: 0.6934 - val_loss: 0.7273 - val_categorical_accuracy: 0.7350 - 870ms/epoch - 6ms/step
Epoch 9/250
141/141 - 1s - loss: 0.7273 - categorical_accuracy: 0.7304 - val_loss: 0.8376 - val_categorical_accuracy: 0.6797 - 860ms/epoch - 6ms/step
Epoch 10/250
141/141 - 1s - loss: 0.6645 - categorical_accuracy: 0.7531 - val_loss: 0.5896 - val_categorical_accuracy: 0.7835 - 850ms/epoch - 6ms/step
Epoch 11/250
141/141 - 1s - loss: 0.6190 - categorical_accuracy: 0.7692 - val_loss: 0.5785 - val_categorical_accuracy: 0.7778 - 850ms/epoch - 6ms/step
Epoch 12/250
141/141 - 1s - loss: 0.8997 - categorical_accuracy: 0.6835 - val_loss: 0.6305 - val_categorical_accuracy: 0.7582 - 850ms/epoch - 6ms/step
Epoch 13/250
141/141 - 1s - loss: 0.6002 - categorical_accuracy: 0.7777 - val_loss: 0.5817 - val_categorical_accuracy: 0.7780 - 850ms/epoch - 6ms/step
Epoch 14/250
141/141 - 1s - loss: 0.5679 - categorical_accuracy: 0.7925 - val_loss: 0.5162 - val_categorical_accuracy: 0.8121 - 840ms/epoch - 6ms/step
Epoch 15/250
141/141 - 1s - loss: 0.5107 - categorical_accuracy: 0.8114 - val_loss: 0.4745 - val_categorical_accuracy: 0.8282 - 840ms/epoch - 6ms/step
Epoch 16/250
141/141 - 1s - loss: 0.4835 - categorical_accuracy: 0.8197 - val_loss: 0.5187 - val_categorical_accuracy: 0.8130 - 840ms/epoch - 6ms/step
Epoch 17/250
141/141 - 1s - loss: 0.4625 - categorical_accuracy: 0.8272 - val_loss: 0.4927 - val_categorical_accuracy: 0.8254 - 860ms/epoch - 6ms/step
Epoch 18/250
141/141 - 1s - loss: 0.4712 - categorical_accuracy: 0.8279 - val_loss: 0.4758 - val_categorical_accuracy: 0.8193 - 860ms/epoch - 6ms/step
Epoch 19/250
141/141 - 1s - loss: 0.4367 - categorical_accuracy: 0.8384 - val_loss: 0.4381 - val_categorical_accuracy: 0.8364 - 860ms/epoch - 6ms/step
Epoch 20/250
141/141 - 1s - loss: 0.5481 - categorical_accuracy: 0.8100 - val_loss: 0.4359 - val_categorical_accuracy: 0.8460 - 860ms/epoch - 6ms/step
Epoch 21/250
141/141 - 1s - loss: 0.4091 - categorical_accuracy: 0.8492 - val_loss: 0.4001 - val_categorical_accuracy: 0.8461 - 860ms/epoch - 6ms/step
Epoch 22/250
141/141 - 1s - loss: 0.4792 - categorical_accuracy: 0.8321 - val_loss: 0.7290 - val_categorical_accuracy: 0.7469 - 860ms/epoch - 6ms/step
Epoch 23/250
141/141 - 1s - loss: 0.3966 - categorical_accuracy: 0.8552 - val_loss: 0.3641 - val_categorical_accuracy: 0.8678 - 850ms/epoch - 6ms/step
Epoch 24/250
141/141 - 1s - loss: 0.3670 - categorical_accuracy: 0.8658 - val_loss: 0.3526 - val_categorical_accuracy: 0.8724 - 870ms/epoch - 6ms/step
Epoch 25/250
141/141 - 1s - loss: 0.3745 - categorical_accuracy: 0.8656 - val_loss: 0.3921 - val_categorical_accuracy: 0.8548 - 860ms/epoch - 6ms/step
Epoch 26/250
141/141 - 1s - loss: 0.3608 - categorical_accuracy: 0.8710 - val_loss: 0.3510 - val_categorical_accuracy: 0.8735 - 860ms/epoch - 6ms/step
Epoch 27/250
141/141 - 1s - loss: 0.3368 - categorical_accuracy: 0.8780 - val_loss: 0.3418 - val_categorical_accuracy: 0.8773 - 860ms/epoch - 6ms/step
Epoch 28/250
141/141 - 1s - loss: 0.3384 - categorical_accuracy: 0.8787 - val_loss: 0.3749 - val_categorical_accuracy: 0.8634 - 860ms/epoch - 6ms/step
Epoch 29/250
141/141 - 1s - loss: 0.3105 - categorical_accuracy: 0.8866 - val_loss: 0.3028 - val_categorical_accuracy: 0.8917 - 860ms/epoch - 6ms/step
Epoch 30/250
141/141 - 1s - loss: 0.3078 - categorical_accuracy: 0.8884 - val_loss: 0.5125 - val_categorical_accuracy: 0.8112 - 850ms/epoch - 6ms/step
Epoch 31/250
141/141 - 1s - loss: 0.3198 - categorical_accuracy: 0.8862 - val_loss: 0.3282 - val_categorical_accuracy: 0.8794 - 850ms/epoch - 6ms/step
Epoch 32/250
141/141 - 1s - loss: 0.3025 - categorical_accuracy: 0.8922 - val_loss: 0.3055 - val_categorical_accuracy: 0.8904 - 850ms/epoch - 6ms/step
Epoch 33/250
141/141 - 1s - loss: 0.2835 - categorical_accuracy: 0.8978 - val_loss: 0.3044 - val_categorical_accuracy: 0.8911 - 850ms/epoch - 6ms/step
Epoch 34/250
141/141 - 1s - loss: 0.2911 - categorical_accuracy: 0.8967 - val_loss: 0.2987 - val_categorical_accuracy: 0.8944 - 850ms/epoch - 6ms/step
Epoch 35/250
141/141 - 1s - loss: 0.3458 - categorical_accuracy: 0.8836 - val_loss: 0.2737 - val_categorical_accuracy: 0.9033 - 860ms/epoch - 6ms/step
Epoch 36/250
141/141 - 1s - loss: 0.2697 - categorical_accuracy: 0.9037 - val_loss: 0.2700 - val_categorical_accuracy: 0.9045 - 850ms/epoch - 6ms/step
Epoch 37/250
141/141 - 1s - loss: 0.2821 - categorical_accuracy: 0.9010 - val_loss: 0.2642 - val_categorical_accuracy: 0.9067 - 850ms/epoch - 6ms/step
Epoch 38/250
141/141 - 1s - loss: 0.2827 - categorical_accuracy: 0.9013 - val_loss: 0.2603 - val_categorical_accuracy: 0.9092 - 840ms/epoch - 6ms/step
Epoch 39/250
141/141 - 1s - loss: 0.2406 - categorical_accuracy: 0.9143 - val_loss: 0.2644 - val_categorical_accuracy: 0.9061 - 860ms/epoch - 6ms/step
Epoch 40/250
141/141 - 1s - loss: 0.2827 - categorical_accuracy: 0.9040 - val_loss: 0.2775 - val_categorical_accuracy: 0.9006 - 870ms/epoch - 6ms/step
Epoch 41/250
141/141 - 1s - loss: 0.2493 - categorical_accuracy: 0.9116 - val_loss: 0.2541 - val_categorical_accuracy: 0.9091 - 850ms/epoch - 6ms/step
Epoch 42/250
141/141 - 1s - loss: 0.2620 - categorical_accuracy: 0.9090 - val_loss: 0.3126 - val_categorical_accuracy: 0.8888 - 860ms/epoch - 6ms/step
Epoch 43/250
141/141 - 1s - loss: 0.2391 - categorical_accuracy: 0.9159 - val_loss: 0.2843 - val_categorical_accuracy: 0.9006 - 850ms/epoch - 6ms/step
Epoch 44/250
141/141 - 1s - loss: 0.2278 - categorical_accuracy: 0.9197 - val_loss: 0.3333 - val_categorical_accuracy: 0.8780 - 1s/epoch - 7ms/step
Epoch 45/250
141/141 - 1s - loss: 0.2288 - categorical_accuracy: 0.9197 - val_loss: 0.2217 - val_categorical_accuracy: 0.9229 - 850ms/epoch - 6ms/step
Epoch 46/250
141/141 - 1s - loss: 0.2163 - categorical_accuracy: 0.9231 - val_loss: 0.2485 - val_categorical_accuracy: 0.9146 - 860ms/epoch - 6ms/step
Epoch 47/250
141/141 - 1s - loss: 0.2131 - categorical_accuracy: 0.9244 - val_loss: 0.2602 - val_categorical_accuracy: 0.9086 - 840ms/epoch - 6ms/step
Epoch 48/250
141/141 - 1s - loss: 0.2070 - categorical_accuracy: 0.9263 - val_loss: 0.3281 - val_categorical_accuracy: 0.8834 - 840ms/epoch - 6ms/step
Epoch 49/250
141/141 - 1s - loss: 0.2118 - categorical_accuracy: 0.9249 - val_loss: 0.2190 - val_categorical_accuracy: 0.9248 - 860ms/epoch - 6ms/step
Epoch 50/250
141/141 - 1s - loss: 0.1999 - categorical_accuracy: 0.9290 - val_loss: 0.2922 - val_categorical_accuracy: 0.9017 - 850ms/epoch - 6ms/step
Epoch 51/250
141/141 - 1s - loss: 0.2700 - categorical_accuracy: 0.9130 - val_loss: 0.2063 - val_categorical_accuracy: 0.9297 - 840ms/epoch - 6ms/step
Epoch 52/250
141/141 - 1s - loss: 0.2350 - categorical_accuracy: 0.9216 - val_loss: 0.2129 - val_categorical_accuracy: 0.9256 - 850ms/epoch - 6ms/step
Epoch 53/250
141/141 - 1s - loss: 0.1910 - categorical_accuracy: 0.9326 - val_loss: 0.2303 - val_categorical_accuracy: 0.9198 - 860ms/epoch - 6ms/step
Epoch 54/250
141/141 - 1s - loss: 0.1948 - categorical_accuracy: 0.9315 - val_loss: 0.2292 - val_categorical_accuracy: 0.9206 - 860ms/epoch - 6ms/step
Epoch 55/250
141/141 - 1s - loss: 0.1984 - categorical_accuracy: 0.9313 - val_loss: 0.2099 - val_categorical_accuracy: 0.9285 - 850ms/epoch - 6ms/step
Epoch 56/250
141/141 - 1s - loss: 0.1936 - categorical_accuracy: 0.9331 - val_loss: 1.5933 - val_categorical_accuracy: 0.6048 - 850ms/epoch - 6ms/step
Epoch 57/250
141/141 - 1s - loss: 0.2019 - categorical_accuracy: 0.9309 - val_loss: 0.4121 - val_categorical_accuracy: 0.8548 - 860ms/epoch - 6ms/step
Epoch 58/250
141/141 - 1s - loss: 0.1905 - categorical_accuracy: 0.9331 - val_loss: 0.2017 - val_categorical_accuracy: 0.9300 - 860ms/epoch - 6ms/step
Epoch 59/250
141/141 - 1s - loss: 0.1785 - categorical_accuracy: 0.9375 - val_loss: 0.2074 - val_categorical_accuracy: 0.9288 - 860ms/epoch - 6ms/step
Epoch 60/250
141/141 - 1s - loss: 0.1767 - categorical_accuracy: 0.9379 - val_loss: 0.2223 - val_categorical_accuracy: 0.9261 - 840ms/epoch - 6ms/step
Epoch 61/250
141/141 - 1s - loss: 0.1765 - categorical_accuracy: 0.9381 - val_loss: 0.2056 - val_categorical_accuracy: 0.9280 - 860ms/epoch - 6ms/step
Epoch 62/250
141/141 - 1s - loss: 0.2461 - categorical_accuracy: 0.9213 - val_loss: 0.1935 - val_categorical_accuracy: 0.9321 - 840ms/epoch - 6ms/step
Epoch 63/250
141/141 - 1s - loss: 0.1655 - categorical_accuracy: 0.9425 - val_loss: 0.1948 - val_categorical_accuracy: 0.9350 - 840ms/epoch - 6ms/step
Epoch 64/250
141/141 - 1s - loss: 0.1852 - categorical_accuracy: 0.9360 - val_loss: 0.1914 - val_categorical_accuracy: 0.9360 - 860ms/epoch - 6ms/step
Epoch 65/250
141/141 - 1s - loss: 0.1627 - categorical_accuracy: 0.9434 - val_loss: 0.2234 - val_categorical_accuracy: 0.9221 - 860ms/epoch - 6ms/step
Epoch 66/250
141/141 - 1s - loss: 0.1651 - categorical_accuracy: 0.9427 - val_loss: 0.2249 - val_categorical_accuracy: 0.9204 - 860ms/epoch - 6ms/step
Epoch 67/250
141/141 - 1s - loss: 0.2144 - categorical_accuracy: 0.9300 - val_loss: 0.1915 - val_categorical_accuracy: 0.9348 - 850ms/epoch - 6ms/step
Epoch 68/250
141/141 - 1s - loss: 0.1653 - categorical_accuracy: 0.9424 - val_loss: 0.1905 - val_categorical_accuracy: 0.9360 - 850ms/epoch - 6ms/step
Epoch 69/250
141/141 - 1s - loss: 0.1887 - categorical_accuracy: 0.9368 - val_loss: 0.1873 - val_categorical_accuracy: 0.9372 - 840ms/epoch - 6ms/step
Epoch 70/250
141/141 - 1s - loss: 0.1596 - categorical_accuracy: 0.9450 - val_loss: 0.1883 - val_categorical_accuracy: 0.9360 - 860ms/epoch - 6ms/step
Epoch 71/250
141/141 - 1s - loss: 0.1514 - categorical_accuracy: 0.9469 - val_loss: 0.6715 - val_categorical_accuracy: 0.7984 - 860ms/epoch - 6ms/step
Epoch 72/250
141/141 - 1s - loss: 0.1736 - categorical_accuracy: 0.9423 - val_loss: 0.2411 - val_categorical_accuracy: 0.9157 - 860ms/epoch - 6ms/step
Epoch 73/250
141/141 - 1s - loss: 0.1551 - categorical_accuracy: 0.9463 - val_loss: 0.1869 - val_categorical_accuracy: 0.9374 - 870ms/epoch - 6ms/step
Epoch 74/250
141/141 - 1s - loss: 0.1461 - categorical_accuracy: 0.9491 - val_loss: 0.1800 - val_categorical_accuracy: 0.9407 - 880ms/epoch - 6ms/step
Epoch 75/250
141/141 - 1s - loss: 0.1812 - categorical_accuracy: 0.9399 - val_loss: 0.1684 - val_categorical_accuracy: 0.9449 - 870ms/epoch - 6ms/step
Epoch 76/250
141/141 - 1s - loss: 0.1616 - categorical_accuracy: 0.9456 - val_loss: 0.1817 - val_categorical_accuracy: 0.9400 - 870ms/epoch - 6ms/step
Epoch 77/250
141/141 - 1s - loss: 0.1787 - categorical_accuracy: 0.9430 - val_loss: 0.4088 - val_categorical_accuracy: 0.8560 - 870ms/epoch - 6ms/step
Epoch 78/250
141/141 - 1s - loss: 0.1514 - categorical_accuracy: 0.9480 - val_loss: 0.1855 - val_categorical_accuracy: 0.9364 - 850ms/epoch - 6ms/step
Epoch 79/250
141/141 - 1s - loss: 0.1388 - categorical_accuracy: 0.9518 - val_loss: 0.4965 - val_categorical_accuracy: 0.8490 - 860ms/epoch - 6ms/step
Epoch 80/250
141/141 - 1s - loss: 0.1448 - categorical_accuracy: 0.9500 - val_loss: 0.5128 - val_categorical_accuracy: 0.8402 - 850ms/epoch - 6ms/step
Epoch 81/250
141/141 - 1s - loss: 0.1390 - categorical_accuracy: 0.9524 - val_loss: 0.2214 - val_categorical_accuracy: 0.9239 - 860ms/epoch - 6ms/step
Epoch 82/250
141/141 - 1s - loss: 0.1386 - categorical_accuracy: 0.9522 - val_loss: 0.1867 - val_categorical_accuracy: 0.9365 - 850ms/epoch - 6ms/step
Epoch 83/250
141/141 - 1s - loss: 0.1428 - categorical_accuracy: 0.9509 - val_loss: 0.1872 - val_categorical_accuracy: 0.9371 - 850ms/epoch - 6ms/step
Epoch 84/250
141/141 - 1s - loss: 0.1394 - categorical_accuracy: 0.9517 - val_loss: 0.1939 - val_categorical_accuracy: 0.9356 - 850ms/epoch - 6ms/step
Epoch 85/250
141/141 - 1s - loss: 0.1582 - categorical_accuracy: 0.9472 - val_loss: 0.1561 - val_categorical_accuracy: 0.9497 - 850ms/epoch - 6ms/step
Epoch 86/250
141/141 - 1s - loss: 0.1337 - categorical_accuracy: 0.9535 - val_loss: 0.1628 - val_categorical_accuracy: 0.9462 - 870ms/epoch - 6ms/step
Epoch 87/250
141/141 - 1s - loss: 0.1376 - categorical_accuracy: 0.9528 - val_loss: 0.1720 - val_categorical_accuracy: 0.9422 - 850ms/epoch - 6ms/step
Epoch 88/250
141/141 - 1s - loss: 0.1246 - categorical_accuracy: 0.9571 - val_loss: 0.1788 - val_categorical_accuracy: 0.9428 - 860ms/epoch - 6ms/step
Epoch 89/250
141/141 - 1s - loss: 0.1574 - categorical_accuracy: 0.9483 - val_loss: 0.2097 - val_categorical_accuracy: 0.9313 - 850ms/epoch - 6ms/step
Epoch 90/250
141/141 - 1s - loss: 0.1676 - categorical_accuracy: 0.9465 - val_loss: 0.1813 - val_categorical_accuracy: 0.9404 - 860ms/epoch - 6ms/step
Epoch 91/250
141/141 - 1s - loss: 0.1318 - categorical_accuracy: 0.9555 - val_loss: 0.2003 - val_categorical_accuracy: 0.9339 - 860ms/epoch - 6ms/step
Epoch 92/250
141/141 - 1s - loss: 0.1183 - categorical_accuracy: 0.9593 - val_loss: 0.1954 - val_categorical_accuracy: 0.9379 - 850ms/epoch - 6ms/step
Epoch 93/250
141/141 - 1s - loss: 0.1295 - categorical_accuracy: 0.9549 - val_loss: 0.1671 - val_categorical_accuracy: 0.9473 - 860ms/epoch - 6ms/step
Epoch 94/250
141/141 - 1s - loss: 0.1225 - categorical_accuracy: 0.9575 - val_loss: 0.1851 - val_categorical_accuracy: 0.9369 - 850ms/epoch - 6ms/step
Epoch 95/250
141/141 - 1s - loss: 0.1712 - categorical_accuracy: 0.9467 - val_loss: 0.2273 - val_categorical_accuracy: 0.9221 - 850ms/epoch - 6ms/step
Epoch 96/250
141/141 - 1s - loss: 0.1209 - categorical_accuracy: 0.9585 - val_loss: 0.1833 - val_categorical_accuracy: 0.9400 - 850ms/epoch - 6ms/step
Epoch 97/250
141/141 - 1s - loss: 0.1162 - categorical_accuracy: 0.9602 - val_loss: 0.1873 - val_categorical_accuracy: 0.9396 - 860ms/epoch - 6ms/step
Epoch 98/250
141/141 - 1s - loss: 0.1485 - categorical_accuracy: 0.9519 - val_loss: 0.7239 - val_categorical_accuracy: 0.7903 - 850ms/epoch - 6ms/step
Epoch 99/250
141/141 - 1s - loss: 0.1242 - categorical_accuracy: 0.9580 - val_loss: 0.1734 - val_categorical_accuracy: 0.9405 - 850ms/epoch - 6ms/step
Epoch 100/250
141/141 - 1s - loss: 0.1145 - categorical_accuracy: 0.9603 - val_loss: 0.1682 - val_categorical_accuracy: 0.9451 - 860ms/epoch - 6ms/step
Epoch 101/250
141/141 - 1s - loss: 0.1223 - categorical_accuracy: 0.9584 - val_loss: 0.1913 - val_categorical_accuracy: 0.9398 - 860ms/epoch - 6ms/step
Epoch 102/250
141/141 - 1s - loss: 0.1103 - categorical_accuracy: 0.9619 - val_loss: 0.1669 - val_categorical_accuracy: 0.9469 - 850ms/epoch - 6ms/step
Epoch 103/250
141/141 - 1s - loss: 0.1266 - categorical_accuracy: 0.9581 - val_loss: 0.1893 - val_categorical_accuracy: 0.9357 - 870ms/epoch - 6ms/step
Epoch 104/250
141/141 - 1s - loss: 0.1478 - categorical_accuracy: 0.9524 - val_loss: 0.1635 - val_categorical_accuracy: 0.9482 - 860ms/epoch - 6ms/step
Epoch 105/250
141/141 - 1s - loss: 0.1104 - categorical_accuracy: 0.9620 - val_loss: 0.1900 - val_categorical_accuracy: 0.9378 - 850ms/epoch - 6ms/step
Epoch 106/250
141/141 - 1s - loss: 0.1104 - categorical_accuracy: 0.9617 - val_loss: 0.1838 - val_categorical_accuracy: 0.9394 - 840ms/epoch - 6ms/step
Epoch 107/250
141/141 - 1s - loss: 0.1259 - categorical_accuracy: 0.9573 - val_loss: 0.2069 - val_categorical_accuracy: 0.9367 - 850ms/epoch - 6ms/step
Epoch 108/250
141/141 - 1s - loss: 0.1159 - categorical_accuracy: 0.9601 - val_loss: 0.1590 - val_categorical_accuracy: 0.9484 - 860ms/epoch - 6ms/step
Epoch 109/250
141/141 - 1s - loss: 0.1023 - categorical_accuracy: 0.9651 - val_loss: 0.1507 - val_categorical_accuracy: 0.9531 - 850ms/epoch - 6ms/step
Epoch 110/250
141/141 - 1s - loss: 0.2151 - categorical_accuracy: 0.9372 - val_loss: 0.1524 - val_categorical_accuracy: 0.9522 - 860ms/epoch - 6ms/step
Epoch 111/250
141/141 - 1s - loss: 0.1129 - categorical_accuracy: 0.9622 - val_loss: 0.1543 - val_categorical_accuracy: 0.9498 - 850ms/epoch - 6ms/step
Epoch 112/250
141/141 - 1s - loss: 0.1045 - categorical_accuracy: 0.9639 - val_loss: 0.1687 - val_categorical_accuracy: 0.9473 - 850ms/epoch - 6ms/step
Epoch 113/250
141/141 - 1s - loss: 0.1397 - categorical_accuracy: 0.9555 - val_loss: 0.1571 - val_categorical_accuracy: 0.9493 - 850ms/epoch - 6ms/step
Epoch 114/250
141/141 - 1s - loss: 0.0986 - categorical_accuracy: 0.9665 - val_loss: 0.1834 - val_categorical_accuracy: 0.9366 - 860ms/epoch - 6ms/step
Epoch 115/250
141/141 - 1s - loss: 0.1257 - categorical_accuracy: 0.9576 - val_loss: 0.1539 - val_categorical_accuracy: 0.9500 - 860ms/epoch - 6ms/step
Epoch 116/250
141/141 - 1s - loss: 0.1319 - categorical_accuracy: 0.9576 - val_loss: 0.1549 - val_categorical_accuracy: 0.9502 - 857ms/epoch - 6ms/step
Epoch 117/250
141/141 - 1s - loss: 0.1117 - categorical_accuracy: 0.9632 - val_loss: 0.1817 - val_categorical_accuracy: 0.9399 - 850ms/epoch - 6ms/step
Epoch 118/250
141/141 - 1s - loss: 0.0965 - categorical_accuracy: 0.9667 - val_loss: 0.1873 - val_categorical_accuracy: 0.9376 - 850ms/epoch - 6ms/step
Epoch 119/250
141/141 - 1s - loss: 0.1058 - categorical_accuracy: 0.9639 - val_loss: 0.1520 - val_categorical_accuracy: 0.9520 - 850ms/epoch - 6ms/step
Epoch 120/250
141/141 - 1s - loss: 0.1079 - categorical_accuracy: 0.9629 - val_loss: 0.1874 - val_categorical_accuracy: 0.9371 - 840ms/epoch - 6ms/step
Epoch 121/250
141/141 - 1s - loss: 0.1218 - categorical_accuracy: 0.9606 - val_loss: 0.1569 - val_categorical_accuracy: 0.9503 - 840ms/epoch - 6ms/step
Epoch 122/250
141/141 - 1s - loss: 0.1069 - categorical_accuracy: 0.9643 - val_loss: 0.1676 - val_categorical_accuracy: 0.9486 - 850ms/epoch - 6ms/step
Epoch 123/250
141/141 - 1s - loss: 0.0899 - categorical_accuracy: 0.9693 - val_loss: 0.1981 - val_categorical_accuracy: 0.9380 - 870ms/epoch - 6ms/step
Epoch 124/250
141/141 - 1s - loss: 0.0992 - categorical_accuracy: 0.9660 - val_loss: 0.1664 - val_categorical_accuracy: 0.9469 - 860ms/epoch - 6ms/step
Epoch 125/250
141/141 - 1s - loss: 0.1111 - categorical_accuracy: 0.9622 - val_loss: 0.2486 - val_categorical_accuracy: 0.9247 - 860ms/epoch - 6ms/step
Epoch 126/250
141/141 - 1s - loss: 0.0906 - categorical_accuracy: 0.9691 - val_loss: 0.1759 - val_categorical_accuracy: 0.9439 - 850ms/epoch - 6ms/step
Epoch 127/250
141/141 - 1s - loss: 0.1241 - categorical_accuracy: 0.9597 - val_loss: 0.1977 - val_categorical_accuracy: 0.9399 - 850ms/epoch - 6ms/step
Epoch 128/250
141/141 - 1s - loss: 0.0945 - categorical_accuracy: 0.9676 - val_loss: 0.1717 - val_categorical_accuracy: 0.9465 - 860ms/epoch - 6ms/step
Epoch 129/250
141/141 - 1s - loss: 0.0899 - categorical_accuracy: 0.9693 - val_loss: 0.1572 - val_categorical_accuracy: 0.9517 - 840ms/epoch - 6ms/step
Epoch 130/250
141/141 - 1s - loss: 0.2777 - categorical_accuracy: 0.9181 - val_loss: 0.1636 - val_categorical_accuracy: 0.9462 - 860ms/epoch - 6ms/step
Epoch 131/250
141/141 - 1s - loss: 0.0974 - categorical_accuracy: 0.9664 - val_loss: 0.1895 - val_categorical_accuracy: 0.9389 - 850ms/epoch - 6ms/step
Epoch 132/250
141/141 - 1s - loss: 0.0900 - categorical_accuracy: 0.9690 - val_loss: 0.2007 - val_categorical_accuracy: 0.9400 - 850ms/epoch - 6ms/step
Epoch 133/250
141/141 - 1s - loss: 0.0975 - categorical_accuracy: 0.9667 - val_loss: 0.1738 - val_categorical_accuracy: 0.9426 - 860ms/epoch - 6ms/step
Epoch 134/250
141/141 - 1s - loss: 0.0932 - categorical_accuracy: 0.9681 - val_loss: 0.1509 - val_categorical_accuracy: 0.9542 - 860ms/epoch - 6ms/step
Epoch 135/250
141/141 - 1s - loss: 0.1611 - categorical_accuracy: 0.9505 - val_loss: 0.1777 - val_categorical_accuracy: 0.9420 - 860ms/epoch - 6ms/step
Epoch 136/250
141/141 - 1s - loss: 0.0923 - categorical_accuracy: 0.9687 - val_loss: 0.2822 - val_categorical_accuracy: 0.9116 - 850ms/epoch - 6ms/step
Epoch 137/250
141/141 - 1s - loss: 0.1033 - categorical_accuracy: 0.9659 - val_loss: 0.1619 - val_categorical_accuracy: 0.9503 - 860ms/epoch - 6ms/step
Epoch 138/250
141/141 - 1s - loss: 0.1028 - categorical_accuracy: 0.9649 - val_loss: 0.1609 - val_categorical_accuracy: 0.9497 - 840ms/epoch - 6ms/step
Epoch 139/250
141/141 - 1s - loss: 0.0825 - categorical_accuracy: 0.9721 - val_loss: 0.1482 - val_categorical_accuracy: 0.9540 - 850ms/epoch - 6ms/step
Epoch 140/250
141/141 - 1s - loss: 0.0936 - categorical_accuracy: 0.9684 - val_loss: 0.2104 - val_categorical_accuracy: 0.9323 - 860ms/epoch - 6ms/step
Epoch 141/250
141/141 - 1s - loss: 0.0848 - categorical_accuracy: 0.9709 - val_loss: 0.2458 - val_categorical_accuracy: 0.9295 - 870ms/epoch - 6ms/step
Epoch 142/250
141/141 - 1s - loss: 0.1571 - categorical_accuracy: 0.9522 - val_loss: 0.1813 - val_categorical_accuracy: 0.9409 - 860ms/epoch - 6ms/step
Epoch 143/250
141/141 - 1s - loss: 0.0901 - categorical_accuracy: 0.9692 - val_loss: 0.1818 - val_categorical_accuracy: 0.9427 - 870ms/epoch - 6ms/step
Epoch 144/250
141/141 - 1s - loss: 0.0905 - categorical_accuracy: 0.9687 - val_loss: 0.2235 - val_categorical_accuracy: 0.9308 - 870ms/epoch - 6ms/step
Epoch 145/250
141/141 - 1s - loss: 0.0869 - categorical_accuracy: 0.9698 - val_loss: 0.1632 - val_categorical_accuracy: 0.9502 - 870ms/epoch - 6ms/step
Epoch 146/250
141/141 - 1s - loss: 0.1153 - categorical_accuracy: 0.9628 - val_loss: 0.1573 - val_categorical_accuracy: 0.9497 - 860ms/epoch - 6ms/step
Epoch 147/250
141/141 - 1s - loss: 0.0942 - categorical_accuracy: 0.9689 - val_loss: 0.1554 - val_categorical_accuracy: 0.9527 - 860ms/epoch - 6ms/step
Epoch 148/250
141/141 - 1s - loss: 0.0836 - categorical_accuracy: 0.9713 - val_loss: 0.1570 - val_categorical_accuracy: 0.9511 - 850ms/epoch - 6ms/step
Epoch 149/250
141/141 - 1s - loss: 0.1105 - categorical_accuracy: 0.9645 - val_loss: 0.1513 - val_categorical_accuracy: 0.9512 - 850ms/epoch - 6ms/step
Epoch 150/250
141/141 - 1s - loss: 0.0803 - categorical_accuracy: 0.9726 - val_loss: 0.1622 - val_categorical_accuracy: 0.9506 - 850ms/epoch - 6ms/step
Epoch 151/250
141/141 - 1s - loss: 0.0783 - categorical_accuracy: 0.9734 - val_loss: 0.1633 - val_categorical_accuracy: 0.9503 - 850ms/epoch - 6ms/step
Epoch 152/250
141/141 - 1s - loss: 0.1333 - categorical_accuracy: 0.9590 - val_loss: 0.1613 - val_categorical_accuracy: 0.9502 - 850ms/epoch - 6ms/step
Epoch 153/250
141/141 - 1s - loss: 0.0792 - categorical_accuracy: 0.9733 - val_loss: 0.1828 - val_categorical_accuracy: 0.9440 - 850ms/epoch - 6ms/step
Epoch 154/250
141/141 - 1s - loss: 0.0902 - categorical_accuracy: 0.9692 - val_loss: 0.1540 - val_categorical_accuracy: 0.9532 - 840ms/epoch - 6ms/step
Epoch 155/250
141/141 - 1s - loss: 0.0785 - categorical_accuracy: 0.9731 - val_loss: 0.1545 - val_categorical_accuracy: 0.9522 - 850ms/epoch - 6ms/step
Epoch 156/250
141/141 - 1s - loss: 0.1451 - categorical_accuracy: 0.9559 - val_loss: 0.1849 - val_categorical_accuracy: 0.9387 - 860ms/epoch - 6ms/step
Epoch 157/250
141/141 - 1s - loss: 0.0832 - categorical_accuracy: 0.9719 - val_loss: 0.1736 - val_categorical_accuracy: 0.9470 - 870ms/epoch - 6ms/step
Epoch 158/250
141/141 - 1s - loss: 0.0780 - categorical_accuracy: 0.9733 - val_loss: 0.1448 - val_categorical_accuracy: 0.9571 - 860ms/epoch - 6ms/step
Epoch 159/250
141/141 - 1s - loss: 0.1060 - categorical_accuracy: 0.9663 - val_loss: 0.1735 - val_categorical_accuracy: 0.9471 - 860ms/epoch - 6ms/step
Epoch 160/250
141/141 - 1s - loss: 0.0989 - categorical_accuracy: 0.9678 - val_loss: 0.1541 - val_categorical_accuracy: 0.9519 - 850ms/epoch - 6ms/step
Epoch 161/250
141/141 - 1s - loss: 0.1170 - categorical_accuracy: 0.9636 - val_loss: 0.1785 - val_categorical_accuracy: 0.9413 - 850ms/epoch - 6ms/step
Epoch 162/250
141/141 - 1s - loss: 0.0811 - categorical_accuracy: 0.9724 - val_loss: 0.1860 - val_categorical_accuracy: 0.9414 - 850ms/epoch - 6ms/step
Epoch 163/250
141/141 - 1s - loss: 0.0942 - categorical_accuracy: 0.9691 - val_loss: 0.5039 - val_categorical_accuracy: 0.8408 - 860ms/epoch - 6ms/step
Epoch 164/250
141/141 - 1s - loss: 0.0882 - categorical_accuracy: 0.9705 - val_loss: 0.1470 - val_categorical_accuracy: 0.9567 - 850ms/epoch - 6ms/step
Epoch 165/250
141/141 - 1s - loss: 0.0803 - categorical_accuracy: 0.9723 - val_loss: 0.1483 - val_categorical_accuracy: 0.9560 - 860ms/epoch - 6ms/step
Epoch 166/250
141/141 - 1s - loss: 0.0787 - categorical_accuracy: 0.9728 - val_loss: 0.2133 - val_categorical_accuracy: 0.9351 - 850ms/epoch - 6ms/step
Epoch 167/250
141/141 - 1s - loss: 0.1390 - categorical_accuracy: 0.9580 - val_loss: 0.2317 - val_categorical_accuracy: 0.9220 - 860ms/epoch - 6ms/step
Epoch 168/250
141/141 - 1s - loss: 0.0848 - categorical_accuracy: 0.9713 - val_loss: 0.1494 - val_categorical_accuracy: 0.9536 - 850ms/epoch - 6ms/step
Epoch 169/250
141/141 - 1s - loss: 0.0746 - categorical_accuracy: 0.9746 - val_loss: 0.7666 - val_categorical_accuracy: 0.8315 - 850ms/epoch - 6ms/step
Epoch 170/250
141/141 - 1s - loss: 0.1928 - categorical_accuracy: 0.9440 - val_loss: 0.1479 - val_categorical_accuracy: 0.9552 - 860ms/epoch - 6ms/step
Epoch 171/250
141/141 - 1s - loss: 0.0758 - categorical_accuracy: 0.9742 - val_loss: 0.1501 - val_categorical_accuracy: 0.9539 - 860ms/epoch - 6ms/step
Epoch 172/250
141/141 - 1s - loss: 0.0797 - categorical_accuracy: 0.9726 - val_loss: 0.1614 - val_categorical_accuracy: 0.9503 - 850ms/epoch - 6ms/step
Epoch 173/250
141/141 - 1s - loss: 0.0759 - categorical_accuracy: 0.9740 - val_loss: 0.1879 - val_categorical_accuracy: 0.9469 - 860ms/epoch - 6ms/step
Epoch 174/250
141/141 - 1s - loss: 0.0908 - categorical_accuracy: 0.9691 - val_loss: 0.1741 - val_categorical_accuracy: 0.9430 - 860ms/epoch - 6ms/step
Epoch 175/250
141/141 - 1s - loss: 0.0741 - categorical_accuracy: 0.9745 - val_loss: 0.1687 - val_categorical_accuracy: 0.9473 - 860ms/epoch - 6ms/step
Epoch 176/250
141/141 - 1s - loss: 0.0775 - categorical_accuracy: 0.9732 - val_loss: 0.1551 - val_categorical_accuracy: 0.9538 - 850ms/epoch - 6ms/step
Epoch 177/250
141/141 - 1s - loss: 0.0742 - categorical_accuracy: 0.9742 - val_loss: 0.1606 - val_categorical_accuracy: 0.9540 - 860ms/epoch - 6ms/step
Epoch 178/250
141/141 - 1s - loss: 0.0725 - categorical_accuracy: 0.9750 - val_loss: 0.1753 - val_categorical_accuracy: 0.9507 - 870ms/epoch - 6ms/step
Epoch 179/250
141/141 - 1s - loss: 0.0833 - categorical_accuracy: 0.9717 - val_loss: 0.3783 - val_categorical_accuracy: 0.8982 - 850ms/epoch - 6ms/step
Epoch 180/250
141/141 - 1s - loss: 0.1020 - categorical_accuracy: 0.9681 - val_loss: 0.9884 - val_categorical_accuracy: 0.7882 - 860ms/epoch - 6ms/step
Epoch 181/250
141/141 - 1s - loss: 0.1031 - categorical_accuracy: 0.9670 - val_loss: 0.1596 - val_categorical_accuracy: 0.9535 - 870ms/epoch - 6ms/step
Epoch 182/250
141/141 - 1s - loss: 0.0767 - categorical_accuracy: 0.9736 - val_loss: 0.1758 - val_categorical_accuracy: 0.9457 - 850ms/epoch - 6ms/step
Epoch 183/250
141/141 - 1s - loss: 0.0705 - categorical_accuracy: 0.9757 - val_loss: 0.1882 - val_categorical_accuracy: 0.9417 - 850ms/epoch - 6ms/step
Epoch 184/250
141/141 - 1s - loss: 0.1969 - categorical_accuracy: 0.9457 - val_loss: 0.2181 - val_categorical_accuracy: 0.9283 - 860ms/epoch - 6ms/step
Epoch 185/250
141/141 - 1s - loss: 0.0867 - categorical_accuracy: 0.9706 - val_loss: 0.1894 - val_categorical_accuracy: 0.9430 - 860ms/epoch - 6ms/step
Epoch 186/250
141/141 - 1s - loss: 0.0726 - categorical_accuracy: 0.9752 - val_loss: 0.1531 - val_categorical_accuracy: 0.9546 - 843ms/epoch - 6ms/step
Epoch 187/250
141/141 - 1s - loss: 0.0803 - categorical_accuracy: 0.9724 - val_loss: 0.1553 - val_categorical_accuracy: 0.9543 - 850ms/epoch - 6ms/step
Epoch 188/250
141/141 - 1s - loss: 0.0697 - categorical_accuracy: 0.9762 - val_loss: 0.1538 - val_categorical_accuracy: 0.9551 - 860ms/epoch - 6ms/step
Epoch 189/250
141/141 - 1s - loss: 0.1256 - categorical_accuracy: 0.9625 - val_loss: 0.2831 - val_categorical_accuracy: 0.9065 - 860ms/epoch - 6ms/step
Epoch 190/250
141/141 - 1s - loss: 0.0803 - categorical_accuracy: 0.9726 - val_loss: 0.1492 - val_categorical_accuracy: 0.9569 - 850ms/epoch - 6ms/step
Epoch 191/250
141/141 - 1s - loss: 0.0897 - categorical_accuracy: 0.9703 - val_loss: 0.1496 - val_categorical_accuracy: 0.9556 - 860ms/epoch - 6ms/step
Epoch 192/250
141/141 - 1s - loss: 0.0690 - categorical_accuracy: 0.9765 - val_loss: 0.2240 - val_categorical_accuracy: 0.9355 - 860ms/epoch - 6ms/step
Epoch 193/250
141/141 - 1s - loss: 0.0837 - categorical_accuracy: 0.9721 - val_loss: 0.1554 - val_categorical_accuracy: 0.9540 - 850ms/epoch - 6ms/step
Epoch 194/250
141/141 - 1s - loss: 0.0669 - categorical_accuracy: 0.9771 - val_loss: 0.1669 - val_categorical_accuracy: 0.9532 - 860ms/epoch - 6ms/step
Epoch 195/250
141/141 - 1s - loss: 0.0680 - categorical_accuracy: 0.9767 - val_loss: 0.1617 - val_categorical_accuracy: 0.9530 - 850ms/epoch - 6ms/step
Epoch 196/250
141/141 - 1s - loss: 0.0844 - categorical_accuracy: 0.9722 - val_loss: 0.1518 - val_categorical_accuracy: 0.9557 - 860ms/epoch - 6ms/step
Epoch 197/250
141/141 - 1s - loss: 0.0742 - categorical_accuracy: 0.9744 - val_loss: 0.1983 - val_categorical_accuracy: 0.9447 - 860ms/epoch - 6ms/step
Epoch 198/250
141/141 - 1s - loss: 0.0682 - categorical_accuracy: 0.9766 - val_loss: 0.1546 - val_categorical_accuracy: 0.9563 - 860ms/epoch - 6ms/step
Epoch 199/250
141/141 - 1s - loss: 0.0671 - categorical_accuracy: 0.9769 - val_loss: 0.1607 - val_categorical_accuracy: 0.9531 - 850ms/epoch - 6ms/step
Epoch 200/250
141/141 - 1s - loss: 0.0667 - categorical_accuracy: 0.9771 - val_loss: 0.1608 - val_categorical_accuracy: 0.9543 - 860ms/epoch - 6ms/step
Epoch 201/250
141/141 - 1s - loss: 0.0986 - categorical_accuracy: 0.9695 - val_loss: 0.1506 - val_categorical_accuracy: 0.9556 - 840ms/epoch - 6ms/step
Epoch 202/250
141/141 - 1s - loss: 0.0684 - categorical_accuracy: 0.9765 - val_loss: 0.1559 - val_categorical_accuracy: 0.9547 - 850ms/epoch - 6ms/step
Epoch 203/250
141/141 - 1s - loss: 0.0724 - categorical_accuracy: 0.9752 - val_loss: 0.1496 - val_categorical_accuracy: 0.9585 - 850ms/epoch - 6ms/step
Epoch 204/250
141/141 - 1s - loss: 0.0990 - categorical_accuracy: 0.9693 - val_loss: 0.1649 - val_categorical_accuracy: 0.9537 - 850ms/epoch - 6ms/step
Epoch 205/250
141/141 - 1s - loss: 0.0656 - categorical_accuracy: 0.9777 - val_loss: 0.1520 - val_categorical_accuracy: 0.9568 - 850ms/epoch - 6ms/step
Epoch 206/250
141/141 - 1s - loss: 0.1144 - categorical_accuracy: 0.9650 - val_loss: 0.1705 - val_categorical_accuracy: 0.9522 - 850ms/epoch - 6ms/step
Epoch 207/250
141/141 - 1s - loss: 0.0655 - categorical_accuracy: 0.9778 - val_loss: 0.1462 - val_categorical_accuracy: 0.9599 - 860ms/epoch - 6ms/step
Epoch 208/250
141/141 - 1s - loss: 0.0669 - categorical_accuracy: 0.9768 - val_loss: 0.2108 - val_categorical_accuracy: 0.9389 - 850ms/epoch - 6ms/step
Epoch 209/250
141/141 - 1s - loss: 0.0678 - categorical_accuracy: 0.9768 - val_loss: 0.1523 - val_categorical_accuracy: 0.9584 - 860ms/epoch - 6ms/step
Epoch 210/250
141/141 - 1s - loss: 0.0685 - categorical_accuracy: 0.9763 - val_loss: 0.1633 - val_categorical_accuracy: 0.9520 - 860ms/epoch - 6ms/step
Epoch 211/250
141/141 - 1s - loss: 0.0633 - categorical_accuracy: 0.9783 - val_loss: 0.1632 - val_categorical_accuracy: 0.9545 - 860ms/epoch - 6ms/step
Epoch 212/250
141/141 - 1s - loss: 0.2141 - categorical_accuracy: 0.9416 - val_loss: 0.3864 - val_categorical_accuracy: 0.8643 - 860ms/epoch - 6ms/step
Epoch 213/250
141/141 - 1s - loss: 0.1165 - categorical_accuracy: 0.9596 - val_loss: 0.1699 - val_categorical_accuracy: 0.9474 - 860ms/epoch - 6ms/step
Epoch 214/250
141/141 - 1s - loss: 0.0675 - categorical_accuracy: 0.9769 - val_loss: 0.1720 - val_categorical_accuracy: 0.9500 - 860ms/epoch - 6ms/step
Epoch 215/250
141/141 - 1s - loss: 0.0682 - categorical_accuracy: 0.9764 - val_loss: 0.1537 - val_categorical_accuracy: 0.9578 - 870ms/epoch - 6ms/step
Epoch 216/250
141/141 - 1s - loss: 0.0647 - categorical_accuracy: 0.9775 - val_loss: 0.1644 - val_categorical_accuracy: 0.9548 - 870ms/epoch - 6ms/step
Epoch 217/250
141/141 - 1s - loss: 0.0671 - categorical_accuracy: 0.9768 - val_loss: 0.1820 - val_categorical_accuracy: 0.9494 - 850ms/epoch - 6ms/step
Epoch 218/250
141/141 - 1s - loss: 0.0634 - categorical_accuracy: 0.9785 - val_loss: 0.1698 - val_categorical_accuracy: 0.9526 - 860ms/epoch - 6ms/step
Epoch 219/250
141/141 - 1s - loss: 0.0651 - categorical_accuracy: 0.9775 - val_loss: 0.1714 - val_categorical_accuracy: 0.9511 - 860ms/epoch - 6ms/step
Epoch 220/250
141/141 - 1s - loss: 0.0627 - categorical_accuracy: 0.9783 - val_loss: 0.1628 - val_categorical_accuracy: 0.9562 - 850ms/epoch - 6ms/step
Epoch 221/250
141/141 - 1s - loss: 0.1356 - categorical_accuracy: 0.9600 - val_loss: 0.1694 - val_categorical_accuracy: 0.9490 - 850ms/epoch - 6ms/step
Epoch 222/250
141/141 - 1s - loss: 0.0656 - categorical_accuracy: 0.9775 - val_loss: 0.1528 - val_categorical_accuracy: 0.9586 - 860ms/epoch - 6ms/step
Epoch 223/250
141/141 - 1s - loss: 0.0614 - categorical_accuracy: 0.9790 - val_loss: 0.1549 - val_categorical_accuracy: 0.9575 - 850ms/epoch - 6ms/step
Epoch 224/250
141/141 - 1s - loss: 0.0628 - categorical_accuracy: 0.9784 - val_loss: 0.1797 - val_categorical_accuracy: 0.9488 - 850ms/epoch - 6ms/step
Epoch 225/250
141/141 - 1s - loss: 0.0921 - categorical_accuracy: 0.9706 - val_loss: 0.1579 - val_categorical_accuracy: 0.9538 - 850ms/epoch - 6ms/step
Epoch 226/250
141/141 - 1s - loss: 0.0631 - categorical_accuracy: 0.9785 - val_loss: 0.1657 - val_categorical_accuracy: 0.9553 - 850ms/epoch - 6ms/step
Epoch 227/250
141/141 - 1s - loss: 0.0629 - categorical_accuracy: 0.9784 - val_loss: 0.1524 - val_categorical_accuracy: 0.9581 - 850ms/epoch - 6ms/step
Epoch 228/250
141/141 - 1s - loss: 0.1113 - categorical_accuracy: 0.9652 - val_loss: 0.1514 - val_categorical_accuracy: 0.9569 - 850ms/epoch - 6ms/step
Epoch 229/250
141/141 - 1s - loss: 0.0607 - categorical_accuracy: 0.9792 - val_loss: 0.1602 - val_categorical_accuracy: 0.9561 - 860ms/epoch - 6ms/step
Epoch 230/250
141/141 - 1s - loss: 0.0619 - categorical_accuracy: 0.9788 - val_loss: 0.1500 - val_categorical_accuracy: 0.9593 - 850ms/epoch - 6ms/step
Epoch 231/250
141/141 - 1s - loss: 0.0665 - categorical_accuracy: 0.9773 - val_loss: 0.2629 - val_categorical_accuracy: 0.9323 - 850ms/epoch - 6ms/step
Epoch 232/250
141/141 - 1s - loss: 0.0610 - categorical_accuracy: 0.9791 - val_loss: 0.1527 - val_categorical_accuracy: 0.9587 - 860ms/epoch - 6ms/step
Epoch 233/250
141/141 - 1s - loss: 0.0970 - categorical_accuracy: 0.9690 - val_loss: 0.1437 - val_categorical_accuracy: 0.9599 - 850ms/epoch - 6ms/step
Epoch 234/250
141/141 - 1s - loss: 0.0595 - categorical_accuracy: 0.9794 - val_loss: 0.1559 - val_categorical_accuracy: 0.9570 - 850ms/epoch - 6ms/step
Epoch 235/250
141/141 - 1s - loss: 0.0602 - categorical_accuracy: 0.9792 - val_loss: 0.1572 - val_categorical_accuracy: 0.9555 - 850ms/epoch - 6ms/step
Epoch 236/250
141/141 - 1s - loss: 0.0693 - categorical_accuracy: 0.9762 - val_loss: 0.1837 - val_categorical_accuracy: 0.9469 - 860ms/epoch - 6ms/step
Epoch 237/250
141/141 - 1s - loss: 0.1155 - categorical_accuracy: 0.9650 - val_loss: 0.1455 - val_categorical_accuracy: 0.9591 - 850ms/epoch - 6ms/step
Epoch 238/250
141/141 - 1s - loss: 0.0606 - categorical_accuracy: 0.9793 - val_loss: 0.1592 - val_categorical_accuracy: 0.9560 - 850ms/epoch - 6ms/step
Epoch 239/250
141/141 - 1s - loss: 0.0606 - categorical_accuracy: 0.9792 - val_loss: 0.1518 - val_categorical_accuracy: 0.9590 - 850ms/epoch - 6ms/step
Epoch 240/250
141/141 - 1s - loss: 0.0615 - categorical_accuracy: 0.9787 - val_loss: 0.1585 - val_categorical_accuracy: 0.9565 - 860ms/epoch - 6ms/step
Epoch 241/250
141/141 - 1s - loss: 0.0610 - categorical_accuracy: 0.9789 - val_loss: 0.1648 - val_categorical_accuracy: 0.9534 - 850ms/epoch - 6ms/step
Epoch 242/250
141/141 - 1s - loss: 0.0693 - categorical_accuracy: 0.9765 - val_loss: 0.1590 - val_categorical_accuracy: 0.9572 - 850ms/epoch - 6ms/step
Epoch 243/250
141/141 - 1s - loss: 0.1035 - categorical_accuracy: 0.9692 - val_loss: 0.1490 - val_categorical_accuracy: 0.9601 - 840ms/epoch - 6ms/step
Epoch 244/250
141/141 - 1s - loss: 0.0603 - categorical_accuracy: 0.9793 - val_loss: 0.1575 - val_categorical_accuracy: 0.9576 - 870ms/epoch - 6ms/step
Epoch 245/250
141/141 - 1s - loss: 0.0577 - categorical_accuracy: 0.9800 - val_loss: 0.1573 - val_categorical_accuracy: 0.9556 - 860ms/epoch - 6ms/step
Epoch 246/250
141/141 - 1s - loss: 0.0597 - categorical_accuracy: 0.9793 - val_loss: 0.1792 - val_categorical_accuracy: 0.9528 - 850ms/epoch - 6ms/step
Epoch 247/250
141/141 - 1s - loss: 0.1158 - categorical_accuracy: 0.9655 - val_loss: 0.1642 - val_categorical_accuracy: 0.9535 - 850ms/epoch - 6ms/step
Epoch 248/250
141/141 - 1s - loss: 0.0613 - categorical_accuracy: 0.9790 - val_loss: 0.1525 - val_categorical_accuracy: 0.9600 - 840ms/epoch - 6ms/step
Epoch 249/250
141/141 - 1s - loss: 0.0595 - categorical_accuracy: 0.9794 - val_loss: 0.1484 - val_categorical_accuracy: 0.9596 - 850ms/epoch - 6ms/step
Epoch 250/250
141/141 - 1s - loss: 0.0582 - categorical_accuracy: 0.9797 - val_loss: 0.1796 - val_categorical_accuracy: 0.9527 - 860ms/epoch - 6ms/step
processing fold # 8 
Epoch 1/250
141/141 - 2s - loss: 1.8877 - categorical_accuracy: 0.2858 - val_loss: 1.7733 - val_categorical_accuracy: 0.3289 - 2s/epoch - 12ms/step
Epoch 2/250
141/141 - 1s - loss: 1.5370 - categorical_accuracy: 0.4159 - val_loss: 1.8345 - val_categorical_accuracy: 0.3121 - 870ms/epoch - 6ms/step
Epoch 3/250
141/141 - 1s - loss: 1.3044 - categorical_accuracy: 0.5062 - val_loss: 1.2239 - val_categorical_accuracy: 0.5561 - 860ms/epoch - 6ms/step
Epoch 4/250
141/141 - 1s - loss: 1.3050 - categorical_accuracy: 0.5240 - val_loss: 2.0046 - val_categorical_accuracy: 0.1944 - 870ms/epoch - 6ms/step
Epoch 5/250
141/141 - 1s - loss: 1.4516 - categorical_accuracy: 0.4516 - val_loss: 1.0592 - val_categorical_accuracy: 0.5972 - 861ms/epoch - 6ms/step
Epoch 6/250
141/141 - 1s - loss: 1.0742 - categorical_accuracy: 0.5944 - val_loss: 1.0358 - val_categorical_accuracy: 0.6025 - 860ms/epoch - 6ms/step
Epoch 7/250
141/141 - 1s - loss: 0.9571 - categorical_accuracy: 0.6395 - val_loss: 0.8884 - val_categorical_accuracy: 0.6602 - 860ms/epoch - 6ms/step
Epoch 8/250
141/141 - 1s - loss: 0.8590 - categorical_accuracy: 0.6746 - val_loss: 0.8959 - val_categorical_accuracy: 0.6612 - 850ms/epoch - 6ms/step
Epoch 9/250
141/141 - 1s - loss: 0.8215 - categorical_accuracy: 0.6932 - val_loss: 0.8337 - val_categorical_accuracy: 0.6791 - 860ms/epoch - 6ms/step
Epoch 10/250
141/141 - 1s - loss: 1.1797 - categorical_accuracy: 0.5938 - val_loss: 1.0923 - val_categorical_accuracy: 0.6088 - 870ms/epoch - 6ms/step
Epoch 11/250
141/141 - 1s - loss: 0.9627 - categorical_accuracy: 0.6524 - val_loss: 0.8173 - val_categorical_accuracy: 0.6923 - 860ms/epoch - 6ms/step
Epoch 12/250
141/141 - 1s - loss: 0.7228 - categorical_accuracy: 0.7273 - val_loss: 0.6640 - val_categorical_accuracy: 0.7469 - 860ms/epoch - 6ms/step
Epoch 13/250
141/141 - 1s - loss: 0.6982 - categorical_accuracy: 0.7391 - val_loss: 0.6548 - val_categorical_accuracy: 0.7522 - 860ms/epoch - 6ms/step
Epoch 14/250
141/141 - 1s - loss: 0.6341 - categorical_accuracy: 0.7600 - val_loss: 0.5852 - val_categorical_accuracy: 0.7776 - 860ms/epoch - 6ms/step
Epoch 15/250
141/141 - 1s - loss: 0.6013 - categorical_accuracy: 0.7746 - val_loss: 0.5685 - val_categorical_accuracy: 0.7828 - 850ms/epoch - 6ms/step
Epoch 16/250
141/141 - 1s - loss: 0.5591 - categorical_accuracy: 0.7876 - val_loss: 0.6244 - val_categorical_accuracy: 0.7527 - 850ms/epoch - 6ms/step
Epoch 17/250
141/141 - 1s - loss: 0.5411 - categorical_accuracy: 0.7960 - val_loss: 0.5736 - val_categorical_accuracy: 0.7749 - 860ms/epoch - 6ms/step
Epoch 18/250
141/141 - 1s - loss: 1.2298 - categorical_accuracy: 0.5759 - val_loss: 0.7558 - val_categorical_accuracy: 0.7272 - 860ms/epoch - 6ms/step
Epoch 19/250
141/141 - 1s - loss: 0.6415 - categorical_accuracy: 0.7620 - val_loss: 0.5870 - val_categorical_accuracy: 0.7806 - 860ms/epoch - 6ms/step
Epoch 20/250
141/141 - 1s - loss: 0.5996 - categorical_accuracy: 0.7838 - val_loss: 0.5412 - val_categorical_accuracy: 0.8058 - 860ms/epoch - 6ms/step
Epoch 21/250
141/141 - 1s - loss: 0.5151 - categorical_accuracy: 0.8084 - val_loss: 0.5141 - val_categorical_accuracy: 0.8035 - 850ms/epoch - 6ms/step
Epoch 22/250
141/141 - 1s - loss: 0.4836 - categorical_accuracy: 0.8202 - val_loss: 0.5140 - val_categorical_accuracy: 0.8061 - 860ms/epoch - 6ms/step
Epoch 23/250
141/141 - 1s - loss: 0.4988 - categorical_accuracy: 0.8190 - val_loss: 0.5315 - val_categorical_accuracy: 0.8124 - 860ms/epoch - 6ms/step
Epoch 24/250
141/141 - 1s - loss: 0.4448 - categorical_accuracy: 0.8371 - val_loss: 0.4170 - val_categorical_accuracy: 0.8475 - 860ms/epoch - 6ms/step
Epoch 25/250
141/141 - 1s - loss: 0.4297 - categorical_accuracy: 0.8414 - val_loss: 0.4062 - val_categorical_accuracy: 0.8551 - 860ms/epoch - 6ms/step
Epoch 26/250
141/141 - 1s - loss: 0.4116 - categorical_accuracy: 0.8484 - val_loss: 0.4596 - val_categorical_accuracy: 0.8266 - 860ms/epoch - 6ms/step
Epoch 27/250
141/141 - 1s - loss: 0.5373 - categorical_accuracy: 0.8179 - val_loss: 0.4185 - val_categorical_accuracy: 0.8474 - 850ms/epoch - 6ms/step
Epoch 28/250
141/141 - 1s - loss: 0.3941 - categorical_accuracy: 0.8562 - val_loss: 0.8202 - val_categorical_accuracy: 0.7337 - 850ms/epoch - 6ms/step
Epoch 29/250
141/141 - 1s - loss: 0.3981 - categorical_accuracy: 0.8568 - val_loss: 0.4057 - val_categorical_accuracy: 0.8501 - 860ms/epoch - 6ms/step
Epoch 30/250
141/141 - 1s - loss: 0.3693 - categorical_accuracy: 0.8640 - val_loss: 0.3386 - val_categorical_accuracy: 0.8763 - 860ms/epoch - 6ms/step
Epoch 31/250
141/141 - 1s - loss: 0.3605 - categorical_accuracy: 0.8695 - val_loss: 0.3550 - val_categorical_accuracy: 0.8688 - 850ms/epoch - 6ms/step
Epoch 32/250
141/141 - 1s - loss: 0.3585 - categorical_accuracy: 0.8699 - val_loss: 0.3672 - val_categorical_accuracy: 0.8642 - 860ms/epoch - 6ms/step
Epoch 33/250
141/141 - 1s - loss: 0.6427 - categorical_accuracy: 0.7926 - val_loss: 0.3797 - val_categorical_accuracy: 0.8666 - 910ms/epoch - 6ms/step
Epoch 34/250
141/141 - 1s - loss: 0.3519 - categorical_accuracy: 0.8733 - val_loss: 0.3640 - val_categorical_accuracy: 0.8657 - 870ms/epoch - 6ms/step
Epoch 35/250
141/141 - 1s - loss: 0.3320 - categorical_accuracy: 0.8799 - val_loss: 0.3293 - val_categorical_accuracy: 0.8835 - 860ms/epoch - 6ms/step
Epoch 36/250
141/141 - 1s - loss: 0.3246 - categorical_accuracy: 0.8825 - val_loss: 0.3389 - val_categorical_accuracy: 0.8797 - 860ms/epoch - 6ms/step
Epoch 37/250
141/141 - 1s - loss: 0.3166 - categorical_accuracy: 0.8860 - val_loss: 0.3240 - val_categorical_accuracy: 0.8834 - 1s/epoch - 7ms/step
Epoch 38/250
141/141 - 1s - loss: 0.3016 - categorical_accuracy: 0.8916 - val_loss: 0.3521 - val_categorical_accuracy: 0.8725 - 860ms/epoch - 6ms/step
Epoch 39/250
141/141 - 1s - loss: 0.6134 - categorical_accuracy: 0.8091 - val_loss: 0.3269 - val_categorical_accuracy: 0.8863 - 860ms/epoch - 6ms/step
Epoch 40/250
141/141 - 1s - loss: 0.3167 - categorical_accuracy: 0.8884 - val_loss: 0.2919 - val_categorical_accuracy: 0.8979 - 860ms/epoch - 6ms/step
Epoch 41/250
141/141 - 1s - loss: 0.2854 - categorical_accuracy: 0.8983 - val_loss: 0.2807 - val_categorical_accuracy: 0.9032 - 850ms/epoch - 6ms/step
Epoch 42/250
141/141 - 1s - loss: 0.2836 - categorical_accuracy: 0.8990 - val_loss: 0.2861 - val_categorical_accuracy: 0.9000 - 860ms/epoch - 6ms/step
Epoch 43/250
141/141 - 1s - loss: 0.2763 - categorical_accuracy: 0.9020 - val_loss: 0.2938 - val_categorical_accuracy: 0.8958 - 870ms/epoch - 6ms/step
Epoch 44/250
141/141 - 1s - loss: 0.2936 - categorical_accuracy: 0.8983 - val_loss: 0.2689 - val_categorical_accuracy: 0.9061 - 850ms/epoch - 6ms/step
Epoch 45/250
141/141 - 1s - loss: 0.2563 - categorical_accuracy: 0.9085 - val_loss: 0.2783 - val_categorical_accuracy: 0.9033 - 860ms/epoch - 6ms/step
Epoch 46/250
141/141 - 1s - loss: 0.2810 - categorical_accuracy: 0.9020 - val_loss: 0.2797 - val_categorical_accuracy: 0.9009 - 860ms/epoch - 6ms/step
Epoch 47/250
141/141 - 1s - loss: 0.2533 - categorical_accuracy: 0.9095 - val_loss: 0.2963 - val_categorical_accuracy: 0.8948 - 860ms/epoch - 6ms/step
Epoch 48/250
141/141 - 1s - loss: 0.2492 - categorical_accuracy: 0.9115 - val_loss: 0.2844 - val_categorical_accuracy: 0.9010 - 850ms/epoch - 6ms/step
Epoch 49/250
141/141 - 1s - loss: 0.2568 - categorical_accuracy: 0.9100 - val_loss: 0.2559 - val_categorical_accuracy: 0.9094 - 860ms/epoch - 6ms/step
Epoch 50/250
141/141 - 1s - loss: 0.2434 - categorical_accuracy: 0.9140 - val_loss: 0.2505 - val_categorical_accuracy: 0.9146 - 850ms/epoch - 6ms/step
Epoch 51/250
141/141 - 1s - loss: 0.4762 - categorical_accuracy: 0.8605 - val_loss: 1.0968 - val_categorical_accuracy: 0.6232 - 870ms/epoch - 6ms/step
Epoch 52/250
141/141 - 1s - loss: 0.3748 - categorical_accuracy: 0.8701 - val_loss: 0.3018 - val_categorical_accuracy: 0.8935 - 860ms/epoch - 6ms/step
Epoch 53/250
141/141 - 1s - loss: 0.2387 - categorical_accuracy: 0.9159 - val_loss: 0.2468 - val_categorical_accuracy: 0.9161 - 860ms/epoch - 6ms/step
Epoch 54/250
141/141 - 1s - loss: 0.2318 - categorical_accuracy: 0.9181 - val_loss: 0.2602 - val_categorical_accuracy: 0.9080 - 860ms/epoch - 6ms/step
Epoch 55/250
141/141 - 1s - loss: 0.2243 - categorical_accuracy: 0.9211 - val_loss: 0.2362 - val_categorical_accuracy: 0.9189 - 860ms/epoch - 6ms/step
Epoch 56/250
141/141 - 1s - loss: 0.2397 - categorical_accuracy: 0.9170 - val_loss: 0.2400 - val_categorical_accuracy: 0.9163 - 860ms/epoch - 6ms/step
Epoch 57/250
141/141 - 1s - loss: 0.2148 - categorical_accuracy: 0.9241 - val_loss: 0.8887 - val_categorical_accuracy: 0.7625 - 860ms/epoch - 6ms/step
Epoch 58/250
141/141 - 1s - loss: 0.2219 - categorical_accuracy: 0.9234 - val_loss: 0.2331 - val_categorical_accuracy: 0.9190 - 870ms/epoch - 6ms/step
Epoch 59/250
141/141 - 1s - loss: 0.2138 - categorical_accuracy: 0.9250 - val_loss: 0.5251 - val_categorical_accuracy: 0.8337 - 870ms/epoch - 6ms/step
Epoch 60/250
141/141 - 1s - loss: 0.2243 - categorical_accuracy: 0.9225 - val_loss: 0.2456 - val_categorical_accuracy: 0.9171 - 850ms/epoch - 6ms/step
Epoch 61/250
141/141 - 1s - loss: 0.2024 - categorical_accuracy: 0.9292 - val_loss: 0.2829 - val_categorical_accuracy: 0.9008 - 860ms/epoch - 6ms/step
Epoch 62/250
141/141 - 1s - loss: 0.2158 - categorical_accuracy: 0.9259 - val_loss: 0.2927 - val_categorical_accuracy: 0.8976 - 850ms/epoch - 6ms/step
Epoch 63/250
141/141 - 1s - loss: 0.1986 - categorical_accuracy: 0.9303 - val_loss: 0.2866 - val_categorical_accuracy: 0.9013 - 860ms/epoch - 6ms/step
Epoch 64/250
141/141 - 1s - loss: 0.2224 - categorical_accuracy: 0.9252 - val_loss: 0.2214 - val_categorical_accuracy: 0.9213 - 850ms/epoch - 6ms/step
Epoch 65/250
141/141 - 1s - loss: 0.1922 - categorical_accuracy: 0.9328 - val_loss: 0.2400 - val_categorical_accuracy: 0.9160 - 870ms/epoch - 6ms/step
Epoch 66/250
141/141 - 1s - loss: 0.1992 - categorical_accuracy: 0.9310 - val_loss: 0.2124 - val_categorical_accuracy: 0.9269 - 870ms/epoch - 6ms/step
Epoch 67/250
141/141 - 1s - loss: 0.2047 - categorical_accuracy: 0.9306 - val_loss: 0.2256 - val_categorical_accuracy: 0.9225 - 860ms/epoch - 6ms/step
Epoch 68/250
141/141 - 1s - loss: 0.1932 - categorical_accuracy: 0.9335 - val_loss: 0.2276 - val_categorical_accuracy: 0.9189 - 850ms/epoch - 6ms/step
Epoch 69/250
141/141 - 1s - loss: 0.1850 - categorical_accuracy: 0.9354 - val_loss: 0.2092 - val_categorical_accuracy: 0.9282 - 870ms/epoch - 6ms/step
Epoch 70/250
141/141 - 1s - loss: 0.1934 - categorical_accuracy: 0.9335 - val_loss: 0.3205 - val_categorical_accuracy: 0.8911 - 860ms/epoch - 6ms/step
Epoch 71/250
141/141 - 1s - loss: 0.1815 - categorical_accuracy: 0.9368 - val_loss: 0.3494 - val_categorical_accuracy: 0.8741 - 860ms/epoch - 6ms/step
Epoch 72/250
141/141 - 1s - loss: 0.1739 - categorical_accuracy: 0.9393 - val_loss: 0.2157 - val_categorical_accuracy: 0.9265 - 870ms/epoch - 6ms/step
Epoch 73/250
141/141 - 1s - loss: 0.1796 - categorical_accuracy: 0.9372 - val_loss: 0.2743 - val_categorical_accuracy: 0.9078 - 870ms/epoch - 6ms/step
Epoch 74/250
141/141 - 1s - loss: 0.2197 - categorical_accuracy: 0.9291 - val_loss: 0.2174 - val_categorical_accuracy: 0.9244 - 860ms/epoch - 6ms/step
Epoch 75/250
141/141 - 1s - loss: 0.1774 - categorical_accuracy: 0.9386 - val_loss: 0.1971 - val_categorical_accuracy: 0.9331 - 861ms/epoch - 6ms/step
Epoch 76/250
141/141 - 1s - loss: 0.1695 - categorical_accuracy: 0.9412 - val_loss: 0.1969 - val_categorical_accuracy: 0.9329 - 860ms/epoch - 6ms/step
Epoch 77/250
141/141 - 1s - loss: 0.1969 - categorical_accuracy: 0.9347 - val_loss: 0.4116 - val_categorical_accuracy: 0.8612 - 850ms/epoch - 6ms/step
Epoch 78/250
141/141 - 1s - loss: 0.1606 - categorical_accuracy: 0.9446 - val_loss: 0.2075 - val_categorical_accuracy: 0.9300 - 860ms/epoch - 6ms/step
Epoch 79/250
141/141 - 1s - loss: 0.1694 - categorical_accuracy: 0.9414 - val_loss: 0.3545 - val_categorical_accuracy: 0.8782 - 860ms/epoch - 6ms/step
Epoch 80/250
141/141 - 1s - loss: 0.1745 - categorical_accuracy: 0.9408 - val_loss: 0.2085 - val_categorical_accuracy: 0.9278 - 860ms/epoch - 6ms/step
Epoch 81/250
141/141 - 1s - loss: 0.1859 - categorical_accuracy: 0.9382 - val_loss: 0.1883 - val_categorical_accuracy: 0.9366 - 860ms/epoch - 6ms/step
Epoch 82/250
141/141 - 1s - loss: 0.1587 - categorical_accuracy: 0.9453 - val_loss: 0.3223 - val_categorical_accuracy: 0.8879 - 870ms/epoch - 6ms/step
Epoch 83/250
141/141 - 1s - loss: 0.1581 - categorical_accuracy: 0.9453 - val_loss: 0.1960 - val_categorical_accuracy: 0.9341 - 860ms/epoch - 6ms/step
Epoch 84/250
141/141 - 1s - loss: 0.1627 - categorical_accuracy: 0.9435 - val_loss: 0.2060 - val_categorical_accuracy: 0.9301 - 850ms/epoch - 6ms/step
Epoch 85/250
141/141 - 1s - loss: 0.1875 - categorical_accuracy: 0.9382 - val_loss: 0.1867 - val_categorical_accuracy: 0.9357 - 860ms/epoch - 6ms/step
Epoch 86/250
141/141 - 1s - loss: 0.1495 - categorical_accuracy: 0.9484 - val_loss: 0.1812 - val_categorical_accuracy: 0.9385 - 860ms/epoch - 6ms/step
Epoch 87/250
141/141 - 1s - loss: 0.1522 - categorical_accuracy: 0.9472 - val_loss: 0.2049 - val_categorical_accuracy: 0.9321 - 860ms/epoch - 6ms/step
Epoch 88/250
141/141 - 1s - loss: 0.1619 - categorical_accuracy: 0.9447 - val_loss: 0.1902 - val_categorical_accuracy: 0.9357 - 860ms/epoch - 6ms/step
Epoch 89/250
141/141 - 1s - loss: 0.1621 - categorical_accuracy: 0.9441 - val_loss: 0.2026 - val_categorical_accuracy: 0.9296 - 860ms/epoch - 6ms/step
Epoch 90/250
141/141 - 1s - loss: 0.1460 - categorical_accuracy: 0.9496 - val_loss: 0.2309 - val_categorical_accuracy: 0.9194 - 850ms/epoch - 6ms/step
Epoch 91/250
141/141 - 1s - loss: 0.1552 - categorical_accuracy: 0.9465 - val_loss: 0.1862 - val_categorical_accuracy: 0.9363 - 860ms/epoch - 6ms/step
Epoch 92/250
141/141 - 1s - loss: 0.1515 - categorical_accuracy: 0.9484 - val_loss: 0.2225 - val_categorical_accuracy: 0.9247 - 850ms/epoch - 6ms/step
Epoch 93/250
141/141 - 1s - loss: 0.1446 - categorical_accuracy: 0.9500 - val_loss: 0.2088 - val_categorical_accuracy: 0.9300 - 850ms/epoch - 6ms/step
Epoch 94/250
141/141 - 1s - loss: 0.1475 - categorical_accuracy: 0.9488 - val_loss: 0.2110 - val_categorical_accuracy: 0.9292 - 860ms/epoch - 6ms/step
Epoch 95/250
141/141 - 1s - loss: 0.2628 - categorical_accuracy: 0.9233 - val_loss: 0.4027 - val_categorical_accuracy: 0.8610 - 850ms/epoch - 6ms/step
Epoch 96/250
141/141 - 1s - loss: 0.1546 - categorical_accuracy: 0.9480 - val_loss: 0.1859 - val_categorical_accuracy: 0.9368 - 860ms/epoch - 6ms/step
Epoch 97/250
141/141 - 1s - loss: 0.1592 - categorical_accuracy: 0.9470 - val_loss: 0.1838 - val_categorical_accuracy: 0.9379 - 870ms/epoch - 6ms/step
Epoch 98/250
141/141 - 1s - loss: 0.1338 - categorical_accuracy: 0.9540 - val_loss: 0.1705 - val_categorical_accuracy: 0.9433 - 870ms/epoch - 6ms/step
Epoch 99/250
141/141 - 1s - loss: 0.1429 - categorical_accuracy: 0.9519 - val_loss: 0.2025 - val_categorical_accuracy: 0.9287 - 860ms/epoch - 6ms/step
Epoch 100/250
141/141 - 1s - loss: 0.1543 - categorical_accuracy: 0.9490 - val_loss: 0.2577 - val_categorical_accuracy: 0.9107 - 860ms/epoch - 6ms/step
Epoch 101/250
141/141 - 1s - loss: 0.1394 - categorical_accuracy: 0.9522 - val_loss: 0.1799 - val_categorical_accuracy: 0.9407 - 850ms/epoch - 6ms/step
Epoch 102/250
141/141 - 1s - loss: 0.1439 - categorical_accuracy: 0.9512 - val_loss: 0.1871 - val_categorical_accuracy: 0.9373 - 870ms/epoch - 6ms/step
Epoch 103/250
141/141 - 1s - loss: 0.1294 - categorical_accuracy: 0.9555 - val_loss: 0.2019 - val_categorical_accuracy: 0.9332 - 860ms/epoch - 6ms/step
Epoch 104/250
141/141 - 1s - loss: 0.1621 - categorical_accuracy: 0.9469 - val_loss: 0.1868 - val_categorical_accuracy: 0.9367 - 870ms/epoch - 6ms/step
Epoch 105/250
141/141 - 1s - loss: 0.1241 - categorical_accuracy: 0.9573 - val_loss: 0.1703 - val_categorical_accuracy: 0.9432 - 860ms/epoch - 6ms/step
Epoch 106/250
141/141 - 1s - loss: 0.1337 - categorical_accuracy: 0.9543 - val_loss: 0.1982 - val_categorical_accuracy: 0.9347 - 860ms/epoch - 6ms/step
Epoch 107/250
141/141 - 1s - loss: 0.1562 - categorical_accuracy: 0.9490 - val_loss: 0.1794 - val_categorical_accuracy: 0.9388 - 860ms/epoch - 6ms/step
Epoch 108/250
141/141 - 1s - loss: 0.1268 - categorical_accuracy: 0.9564 - val_loss: 0.1863 - val_categorical_accuracy: 0.9364 - 870ms/epoch - 6ms/step
Epoch 109/250
141/141 - 1s - loss: 0.1390 - categorical_accuracy: 0.9527 - val_loss: 0.1805 - val_categorical_accuracy: 0.9412 - 860ms/epoch - 6ms/step
Epoch 110/250
141/141 - 1s - loss: 0.1256 - categorical_accuracy: 0.9563 - val_loss: 0.1767 - val_categorical_accuracy: 0.9419 - 850ms/epoch - 6ms/step
Epoch 111/250
141/141 - 1s - loss: 0.1258 - categorical_accuracy: 0.9565 - val_loss: 0.2024 - val_categorical_accuracy: 0.9327 - 860ms/epoch - 6ms/step
Epoch 112/250
141/141 - 1s - loss: 0.1230 - categorical_accuracy: 0.9579 - val_loss: 0.1724 - val_categorical_accuracy: 0.9448 - 860ms/epoch - 6ms/step
Epoch 113/250
141/141 - 1s - loss: 0.1599 - categorical_accuracy: 0.9479 - val_loss: 0.1977 - val_categorical_accuracy: 0.9343 - 870ms/epoch - 6ms/step
Epoch 114/250
141/141 - 1s - loss: 0.1174 - categorical_accuracy: 0.9603 - val_loss: 0.2145 - val_categorical_accuracy: 0.9294 - 860ms/epoch - 6ms/step
Epoch 115/250
141/141 - 1s - loss: 0.1229 - categorical_accuracy: 0.9575 - val_loss: 0.1829 - val_categorical_accuracy: 0.9412 - 860ms/epoch - 6ms/step
Epoch 116/250
141/141 - 1s - loss: 0.1668 - categorical_accuracy: 0.9478 - val_loss: 0.2033 - val_categorical_accuracy: 0.9334 - 850ms/epoch - 6ms/step
Epoch 117/250
141/141 - 1s - loss: 0.1173 - categorical_accuracy: 0.9597 - val_loss: 0.1887 - val_categorical_accuracy: 0.9385 - 860ms/epoch - 6ms/step
Epoch 118/250
141/141 - 1s - loss: 0.1208 - categorical_accuracy: 0.9581 - val_loss: 0.1767 - val_categorical_accuracy: 0.9428 - 860ms/epoch - 6ms/step
Epoch 119/250
141/141 - 1s - loss: 0.1533 - categorical_accuracy: 0.9502 - val_loss: 0.1939 - val_categorical_accuracy: 0.9339 - 860ms/epoch - 6ms/step
Epoch 120/250
141/141 - 1s - loss: 0.1116 - categorical_accuracy: 0.9618 - val_loss: 0.2113 - val_categorical_accuracy: 0.9340 - 860ms/epoch - 6ms/step
Epoch 121/250
141/141 - 1s - loss: 0.1258 - categorical_accuracy: 0.9570 - val_loss: 0.1812 - val_categorical_accuracy: 0.9416 - 860ms/epoch - 6ms/step
Epoch 122/250
141/141 - 1s - loss: 0.1125 - categorical_accuracy: 0.9616 - val_loss: 0.1745 - val_categorical_accuracy: 0.9432 - 860ms/epoch - 6ms/step
Epoch 123/250
141/141 - 1s - loss: 0.2818 - categorical_accuracy: 0.9210 - val_loss: 0.2391 - val_categorical_accuracy: 0.9191 - 850ms/epoch - 6ms/step
Epoch 124/250
141/141 - 1s - loss: 0.1310 - categorical_accuracy: 0.9559 - val_loss: 0.1795 - val_categorical_accuracy: 0.9406 - 870ms/epoch - 6ms/step
Epoch 125/250
141/141 - 1s - loss: 0.1200 - categorical_accuracy: 0.9592 - val_loss: 0.1728 - val_categorical_accuracy: 0.9431 - 860ms/epoch - 6ms/step
Epoch 126/250
141/141 - 1s - loss: 0.1124 - categorical_accuracy: 0.9614 - val_loss: 0.2287 - val_categorical_accuracy: 0.9237 - 860ms/epoch - 6ms/step
Epoch 127/250
141/141 - 1s - loss: 0.1212 - categorical_accuracy: 0.9592 - val_loss: 0.1688 - val_categorical_accuracy: 0.9461 - 870ms/epoch - 6ms/step
Epoch 128/250
141/141 - 1s - loss: 0.1273 - categorical_accuracy: 0.9579 - val_loss: 0.1675 - val_categorical_accuracy: 0.9460 - 860ms/epoch - 6ms/step
Epoch 129/250
141/141 - 1s - loss: 0.1074 - categorical_accuracy: 0.9631 - val_loss: 0.1710 - val_categorical_accuracy: 0.9466 - 870ms/epoch - 6ms/step
Epoch 130/250
141/141 - 1s - loss: 0.1314 - categorical_accuracy: 0.9563 - val_loss: 0.2077 - val_categorical_accuracy: 0.9301 - 860ms/epoch - 6ms/step
Epoch 131/250
141/141 - 1s - loss: 0.1079 - categorical_accuracy: 0.9636 - val_loss: 0.1737 - val_categorical_accuracy: 0.9439 - 870ms/epoch - 6ms/step
Epoch 132/250
141/141 - 1s - loss: 0.1256 - categorical_accuracy: 0.9580 - val_loss: 0.1941 - val_categorical_accuracy: 0.9369 - 860ms/epoch - 6ms/step
Epoch 133/250
141/141 - 1s - loss: 0.1061 - categorical_accuracy: 0.9637 - val_loss: 0.1651 - val_categorical_accuracy: 0.9485 - 860ms/epoch - 6ms/step
Epoch 134/250
141/141 - 1s - loss: 0.1158 - categorical_accuracy: 0.9608 - val_loss: 0.1718 - val_categorical_accuracy: 0.9433 - 850ms/epoch - 6ms/step
Epoch 135/250
141/141 - 1s - loss: 0.1140 - categorical_accuracy: 0.9615 - val_loss: 0.4187 - val_categorical_accuracy: 0.8739 - 880ms/epoch - 6ms/step
Epoch 136/250
141/141 - 1s - loss: 0.1051 - categorical_accuracy: 0.9644 - val_loss: 0.1635 - val_categorical_accuracy: 0.9483 - 850ms/epoch - 6ms/step
Epoch 137/250
141/141 - 1s - loss: 0.1471 - categorical_accuracy: 0.9545 - val_loss: 0.2094 - val_categorical_accuracy: 0.9291 - 850ms/epoch - 6ms/step
Epoch 138/250
141/141 - 1s - loss: 0.1184 - categorical_accuracy: 0.9606 - val_loss: 0.1715 - val_categorical_accuracy: 0.9459 - 850ms/epoch - 6ms/step
Epoch 139/250
141/141 - 1s - loss: 0.0991 - categorical_accuracy: 0.9664 - val_loss: 0.1874 - val_categorical_accuracy: 0.9393 - 850ms/epoch - 6ms/step
Epoch 140/250
141/141 - 1s - loss: 0.1048 - categorical_accuracy: 0.9639 - val_loss: 0.1690 - val_categorical_accuracy: 0.9478 - 858ms/epoch - 6ms/step
Epoch 141/250
141/141 - 1s - loss: 0.1054 - categorical_accuracy: 0.9638 - val_loss: 0.2272 - val_categorical_accuracy: 0.9306 - 860ms/epoch - 6ms/step
Epoch 142/250
141/141 - 1s - loss: 0.1050 - categorical_accuracy: 0.9640 - val_loss: 0.1656 - val_categorical_accuracy: 0.9485 - 870ms/epoch - 6ms/step
Epoch 143/250
141/141 - 1s - loss: 0.1021 - categorical_accuracy: 0.9655 - val_loss: 0.1804 - val_categorical_accuracy: 0.9463 - 850ms/epoch - 6ms/step
Epoch 144/250
141/141 - 1s - loss: 0.1201 - categorical_accuracy: 0.9605 - val_loss: 0.1777 - val_categorical_accuracy: 0.9436 - 860ms/epoch - 6ms/step
Epoch 145/250
141/141 - 1s - loss: 0.1158 - categorical_accuracy: 0.9613 - val_loss: 0.1608 - val_categorical_accuracy: 0.9502 - 850ms/epoch - 6ms/step
Epoch 146/250
141/141 - 1s - loss: 0.0946 - categorical_accuracy: 0.9678 - val_loss: 0.1927 - val_categorical_accuracy: 0.9374 - 860ms/epoch - 6ms/step
Epoch 147/250
141/141 - 1s - loss: 0.1361 - categorical_accuracy: 0.9575 - val_loss: 0.1795 - val_categorical_accuracy: 0.9438 - 860ms/epoch - 6ms/step
Epoch 148/250
141/141 - 1s - loss: 0.0953 - categorical_accuracy: 0.9675 - val_loss: 0.2044 - val_categorical_accuracy: 0.9316 - 860ms/epoch - 6ms/step
Epoch 149/250
141/141 - 1s - loss: 0.1019 - categorical_accuracy: 0.9655 - val_loss: 0.1703 - val_categorical_accuracy: 0.9464 - 870ms/epoch - 6ms/step
Epoch 150/250
141/141 - 1s - loss: 0.1146 - categorical_accuracy: 0.9624 - val_loss: 0.1877 - val_categorical_accuracy: 0.9385 - 850ms/epoch - 6ms/step
Epoch 151/250
141/141 - 1s - loss: 0.0968 - categorical_accuracy: 0.9669 - val_loss: 0.1729 - val_categorical_accuracy: 0.9448 - 860ms/epoch - 6ms/step
Epoch 152/250
141/141 - 1s - loss: 0.1606 - categorical_accuracy: 0.9522 - val_loss: 0.1598 - val_categorical_accuracy: 0.9498 - 850ms/epoch - 6ms/step
Epoch 153/250
141/141 - 1s - loss: 0.0927 - categorical_accuracy: 0.9691 - val_loss: 0.1983 - val_categorical_accuracy: 0.9375 - 860ms/epoch - 6ms/step
Epoch 154/250
141/141 - 1s - loss: 0.1562 - categorical_accuracy: 0.9531 - val_loss: 0.2022 - val_categorical_accuracy: 0.9332 - 850ms/epoch - 6ms/step
Epoch 155/250
141/141 - 1s - loss: 0.0960 - categorical_accuracy: 0.9678 - val_loss: 0.1598 - val_categorical_accuracy: 0.9503 - 860ms/epoch - 6ms/step
Epoch 156/250
141/141 - 1s - loss: 0.0925 - categorical_accuracy: 0.9684 - val_loss: 0.1680 - val_categorical_accuracy: 0.9483 - 860ms/epoch - 6ms/step
Epoch 157/250
141/141 - 1s - loss: 0.1046 - categorical_accuracy: 0.9647 - val_loss: 1.4546 - val_categorical_accuracy: 0.7272 - 860ms/epoch - 6ms/step
Epoch 158/250
141/141 - 1s - loss: 0.1290 - categorical_accuracy: 0.9588 - val_loss: 0.2032 - val_categorical_accuracy: 0.9356 - 850ms/epoch - 6ms/step
Epoch 159/250
141/141 - 1s - loss: 0.1049 - categorical_accuracy: 0.9652 - val_loss: 0.1568 - val_categorical_accuracy: 0.9521 - 860ms/epoch - 6ms/step
Epoch 160/250
141/141 - 1s - loss: 0.0913 - categorical_accuracy: 0.9694 - val_loss: 0.1659 - val_categorical_accuracy: 0.9482 - 860ms/epoch - 6ms/step
Epoch 161/250
141/141 - 1s - loss: 0.0883 - categorical_accuracy: 0.9700 - val_loss: 0.1869 - val_categorical_accuracy: 0.9393 - 860ms/epoch - 6ms/step
Epoch 162/250
141/141 - 1s - loss: 0.1257 - categorical_accuracy: 0.9601 - val_loss: 0.1610 - val_categorical_accuracy: 0.9479 - 860ms/epoch - 6ms/step
Epoch 163/250
141/141 - 1s - loss: 0.1001 - categorical_accuracy: 0.9664 - val_loss: 0.1602 - val_categorical_accuracy: 0.9511 - 860ms/epoch - 6ms/step
Epoch 164/250
141/141 - 1s - loss: 0.0961 - categorical_accuracy: 0.9676 - val_loss: 0.1653 - val_categorical_accuracy: 0.9492 - 860ms/epoch - 6ms/step
Epoch 165/250
141/141 - 1s - loss: 0.0928 - categorical_accuracy: 0.9684 - val_loss: 0.2536 - val_categorical_accuracy: 0.9166 - 860ms/epoch - 6ms/step
Epoch 166/250
141/141 - 1s - loss: 0.0921 - categorical_accuracy: 0.9687 - val_loss: 0.1860 - val_categorical_accuracy: 0.9429 - 870ms/epoch - 6ms/step
Epoch 167/250
141/141 - 1s - loss: 0.0960 - categorical_accuracy: 0.9674 - val_loss: 0.1736 - val_categorical_accuracy: 0.9487 - 860ms/epoch - 6ms/step
Epoch 168/250
141/141 - 1s - loss: 0.0910 - categorical_accuracy: 0.9689 - val_loss: 0.1722 - val_categorical_accuracy: 0.9468 - 870ms/epoch - 6ms/step
Epoch 169/250
141/141 - 1s - loss: 0.1625 - categorical_accuracy: 0.9515 - val_loss: 0.1714 - val_categorical_accuracy: 0.9448 - 870ms/epoch - 6ms/step
Epoch 170/250
141/141 - 1s - loss: 0.0879 - categorical_accuracy: 0.9705 - val_loss: 0.1739 - val_categorical_accuracy: 0.9472 - 860ms/epoch - 6ms/step
Epoch 171/250
141/141 - 1s - loss: 0.0901 - categorical_accuracy: 0.9690 - val_loss: 0.1662 - val_categorical_accuracy: 0.9485 - 890ms/epoch - 6ms/step
Epoch 172/250
141/141 - 1s - loss: 0.0890 - categorical_accuracy: 0.9697 - val_loss: 0.1871 - val_categorical_accuracy: 0.9399 - 870ms/epoch - 6ms/step
Epoch 173/250
141/141 - 1s - loss: 0.0875 - categorical_accuracy: 0.9703 - val_loss: 0.3155 - val_categorical_accuracy: 0.9079 - 870ms/epoch - 6ms/step
Epoch 174/250
141/141 - 1s - loss: 0.0930 - categorical_accuracy: 0.9684 - val_loss: 0.1646 - val_categorical_accuracy: 0.9512 - 870ms/epoch - 6ms/step
Epoch 175/250
141/141 - 1s - loss: 0.0867 - categorical_accuracy: 0.9703 - val_loss: 0.1582 - val_categorical_accuracy: 0.9533 - 870ms/epoch - 6ms/step
Epoch 176/250
141/141 - 1s - loss: 0.0945 - categorical_accuracy: 0.9680 - val_loss: 0.1853 - val_categorical_accuracy: 0.9424 - 860ms/epoch - 6ms/step
Epoch 177/250
141/141 - 1s - loss: 0.0869 - categorical_accuracy: 0.9700 - val_loss: 0.1715 - val_categorical_accuracy: 0.9477 - 860ms/epoch - 6ms/step
Epoch 178/250
141/141 - 1s - loss: 0.1186 - categorical_accuracy: 0.9630 - val_loss: 0.1653 - val_categorical_accuracy: 0.9489 - 870ms/epoch - 6ms/step
Epoch 179/250
141/141 - 1s - loss: 0.0858 - categorical_accuracy: 0.9709 - val_loss: 0.1669 - val_categorical_accuracy: 0.9499 - 850ms/epoch - 6ms/step
Epoch 180/250
141/141 - 1s - loss: 0.1017 - categorical_accuracy: 0.9664 - val_loss: 0.1758 - val_categorical_accuracy: 0.9482 - 850ms/epoch - 6ms/step
Epoch 181/250
141/141 - 1s - loss: 0.0848 - categorical_accuracy: 0.9712 - val_loss: 0.1552 - val_categorical_accuracy: 0.9541 - 850ms/epoch - 6ms/step
Epoch 182/250
141/141 - 1s - loss: 0.0847 - categorical_accuracy: 0.9707 - val_loss: 0.1619 - val_categorical_accuracy: 0.9509 - 870ms/epoch - 6ms/step
Epoch 183/250
141/141 - 1s - loss: 0.0832 - categorical_accuracy: 0.9716 - val_loss: 0.1623 - val_categorical_accuracy: 0.9531 - 850ms/epoch - 6ms/step
Epoch 184/250
141/141 - 1s - loss: 0.0855 - categorical_accuracy: 0.9709 - val_loss: 0.1520 - val_categorical_accuracy: 0.9546 - 850ms/epoch - 6ms/step
Epoch 185/250
141/141 - 1s - loss: 0.1044 - categorical_accuracy: 0.9648 - val_loss: 0.1738 - val_categorical_accuracy: 0.9465 - 860ms/epoch - 6ms/step
Epoch 186/250
141/141 - 1s - loss: 0.0810 - categorical_accuracy: 0.9724 - val_loss: 0.1894 - val_categorical_accuracy: 0.9449 - 870ms/epoch - 6ms/step
Epoch 187/250
141/141 - 1s - loss: 0.0833 - categorical_accuracy: 0.9715 - val_loss: 0.2026 - val_categorical_accuracy: 0.9403 - 870ms/epoch - 6ms/step
Epoch 188/250
141/141 - 1s - loss: 0.0843 - categorical_accuracy: 0.9710 - val_loss: 0.1765 - val_categorical_accuracy: 0.9473 - 860ms/epoch - 6ms/step
Epoch 189/250
141/141 - 1s - loss: 0.2590 - categorical_accuracy: 0.9320 - val_loss: 0.1586 - val_categorical_accuracy: 0.9530 - 860ms/epoch - 6ms/step
Epoch 190/250
141/141 - 1s - loss: 0.0837 - categorical_accuracy: 0.9715 - val_loss: 0.1540 - val_categorical_accuracy: 0.9552 - 850ms/epoch - 6ms/step
Epoch 191/250
141/141 - 1s - loss: 0.1185 - categorical_accuracy: 0.9639 - val_loss: 0.2348 - val_categorical_accuracy: 0.9243 - 860ms/epoch - 6ms/step
Epoch 192/250
141/141 - 1s - loss: 0.0888 - categorical_accuracy: 0.9698 - val_loss: 0.1677 - val_categorical_accuracy: 0.9503 - 860ms/epoch - 6ms/step
Epoch 193/250
141/141 - 1s - loss: 0.1068 - categorical_accuracy: 0.9657 - val_loss: 0.1530 - val_categorical_accuracy: 0.9521 - 870ms/epoch - 6ms/step
Epoch 194/250
141/141 - 1s - loss: 0.0787 - categorical_accuracy: 0.9735 - val_loss: 0.1693 - val_categorical_accuracy: 0.9482 - 860ms/epoch - 6ms/step
Epoch 195/250
141/141 - 1s - loss: 0.0812 - categorical_accuracy: 0.9722 - val_loss: 0.1790 - val_categorical_accuracy: 0.9445 - 860ms/epoch - 6ms/step
Epoch 196/250
141/141 - 1s - loss: 0.0813 - categorical_accuracy: 0.9721 - val_loss: 0.1697 - val_categorical_accuracy: 0.9514 - 860ms/epoch - 6ms/step
Epoch 197/250
141/141 - 1s - loss: 0.0899 - categorical_accuracy: 0.9699 - val_loss: 0.1888 - val_categorical_accuracy: 0.9395 - 870ms/epoch - 6ms/step
Epoch 198/250
141/141 - 1s - loss: 0.0874 - categorical_accuracy: 0.9703 - val_loss: 0.2026 - val_categorical_accuracy: 0.9394 - 860ms/epoch - 6ms/step
Epoch 199/250
141/141 - 1s - loss: 0.1030 - categorical_accuracy: 0.9666 - val_loss: 0.1943 - val_categorical_accuracy: 0.9363 - 860ms/epoch - 6ms/step
Epoch 200/250
141/141 - 1s - loss: 0.0783 - categorical_accuracy: 0.9735 - val_loss: 0.1575 - val_categorical_accuracy: 0.9535 - 870ms/epoch - 6ms/step
Epoch 201/250
141/141 - 1s - loss: 0.0776 - categorical_accuracy: 0.9736 - val_loss: 0.1751 - val_categorical_accuracy: 0.9467 - 860ms/epoch - 6ms/step
Epoch 202/250
141/141 - 1s - loss: 0.1181 - categorical_accuracy: 0.9625 - val_loss: 0.1615 - val_categorical_accuracy: 0.9518 - 870ms/epoch - 6ms/step
Epoch 203/250
141/141 - 1s - loss: 0.0787 - categorical_accuracy: 0.9735 - val_loss: 0.1679 - val_categorical_accuracy: 0.9492 - 860ms/epoch - 6ms/step
Epoch 204/250
141/141 - 1s - loss: 0.0911 - categorical_accuracy: 0.9694 - val_loss: 0.1538 - val_categorical_accuracy: 0.9545 - 870ms/epoch - 6ms/step
Epoch 205/250
141/141 - 1s - loss: 0.0763 - categorical_accuracy: 0.9738 - val_loss: 0.1897 - val_categorical_accuracy: 0.9441 - 860ms/epoch - 6ms/step
Epoch 206/250
141/141 - 1s - loss: 0.1208 - categorical_accuracy: 0.9632 - val_loss: 0.1586 - val_categorical_accuracy: 0.9524 - 860ms/epoch - 6ms/step
Epoch 207/250
141/141 - 1s - loss: 0.0767 - categorical_accuracy: 0.9739 - val_loss: 0.1680 - val_categorical_accuracy: 0.9501 - 850ms/epoch - 6ms/step
Epoch 208/250
141/141 - 1s - loss: 0.0774 - categorical_accuracy: 0.9737 - val_loss: 0.1671 - val_categorical_accuracy: 0.9512 - 860ms/epoch - 6ms/step
Epoch 209/250
141/141 - 1s - loss: 0.0829 - categorical_accuracy: 0.9718 - val_loss: 0.1569 - val_categorical_accuracy: 0.9549 - 860ms/epoch - 6ms/step
Epoch 210/250
141/141 - 1s - loss: 0.0754 - categorical_accuracy: 0.9741 - val_loss: 0.1716 - val_categorical_accuracy: 0.9487 - 860ms/epoch - 6ms/step
Epoch 211/250
141/141 - 1s - loss: 0.0805 - categorical_accuracy: 0.9724 - val_loss: 0.1625 - val_categorical_accuracy: 0.9542 - 870ms/epoch - 6ms/step
Epoch 212/250
141/141 - 1s - loss: 0.1022 - categorical_accuracy: 0.9673 - val_loss: 0.1630 - val_categorical_accuracy: 0.9518 - 860ms/epoch - 6ms/step
Epoch 213/250
141/141 - 1s - loss: 0.0743 - categorical_accuracy: 0.9746 - val_loss: 0.1830 - val_categorical_accuracy: 0.9489 - 860ms/epoch - 6ms/step
Epoch 214/250
141/141 - 1s - loss: 0.0795 - categorical_accuracy: 0.9731 - val_loss: 0.1725 - val_categorical_accuracy: 0.9496 - 858ms/epoch - 6ms/step
Epoch 215/250
141/141 - 1s - loss: 0.1033 - categorical_accuracy: 0.9666 - val_loss: 0.1949 - val_categorical_accuracy: 0.9387 - 870ms/epoch - 6ms/step
Epoch 216/250
141/141 - 1s - loss: 0.0769 - categorical_accuracy: 0.9739 - val_loss: 0.1733 - val_categorical_accuracy: 0.9496 - 850ms/epoch - 6ms/step
Epoch 217/250
141/141 - 1s - loss: 0.0912 - categorical_accuracy: 0.9698 - val_loss: 0.1676 - val_categorical_accuracy: 0.9487 - 860ms/epoch - 6ms/step
Epoch 218/250
141/141 - 1s - loss: 0.0724 - categorical_accuracy: 0.9753 - val_loss: 0.1937 - val_categorical_accuracy: 0.9396 - 860ms/epoch - 6ms/step
Epoch 219/250
141/141 - 1s - loss: 0.0744 - categorical_accuracy: 0.9744 - val_loss: 0.1788 - val_categorical_accuracy: 0.9470 - 860ms/epoch - 6ms/step
Epoch 220/250
141/141 - 1s - loss: 0.1226 - categorical_accuracy: 0.9621 - val_loss: 0.1502 - val_categorical_accuracy: 0.9576 - 850ms/epoch - 6ms/step
Epoch 221/250
141/141 - 1s - loss: 0.0734 - categorical_accuracy: 0.9752 - val_loss: 0.1696 - val_categorical_accuracy: 0.9508 - 860ms/epoch - 6ms/step
Epoch 222/250
141/141 - 1s - loss: 0.0803 - categorical_accuracy: 0.9730 - val_loss: 0.1612 - val_categorical_accuracy: 0.9529 - 870ms/epoch - 6ms/step
Epoch 223/250
141/141 - 1s - loss: 0.0723 - categorical_accuracy: 0.9753 - val_loss: 0.1908 - val_categorical_accuracy: 0.9429 - 860ms/epoch - 6ms/step
Epoch 224/250
141/141 - 1s - loss: 0.0797 - categorical_accuracy: 0.9726 - val_loss: 0.1761 - val_categorical_accuracy: 0.9485 - 860ms/epoch - 6ms/step
Epoch 225/250
141/141 - 1s - loss: 0.0749 - categorical_accuracy: 0.9744 - val_loss: 0.1780 - val_categorical_accuracy: 0.9513 - 860ms/epoch - 6ms/step
Epoch 226/250
141/141 - 1s - loss: 0.0715 - categorical_accuracy: 0.9754 - val_loss: 0.1791 - val_categorical_accuracy: 0.9499 - 870ms/epoch - 6ms/step
Epoch 227/250
141/141 - 1s - loss: 0.0720 - categorical_accuracy: 0.9753 - val_loss: 0.1716 - val_categorical_accuracy: 0.9535 - 860ms/epoch - 6ms/step
Epoch 228/250
141/141 - 1s - loss: 0.1230 - categorical_accuracy: 0.9625 - val_loss: 0.1583 - val_categorical_accuracy: 0.9530 - 860ms/epoch - 6ms/step
Epoch 229/250
141/141 - 1s - loss: 0.0711 - categorical_accuracy: 0.9761 - val_loss: 0.1533 - val_categorical_accuracy: 0.9584 - 860ms/epoch - 6ms/step
Epoch 230/250
141/141 - 1s - loss: 0.0727 - categorical_accuracy: 0.9748 - val_loss: 0.1699 - val_categorical_accuracy: 0.9501 - 870ms/epoch - 6ms/step
Epoch 231/250
141/141 - 1s - loss: 0.0714 - categorical_accuracy: 0.9754 - val_loss: 0.1665 - val_categorical_accuracy: 0.9531 - 870ms/epoch - 6ms/step
Epoch 232/250
141/141 - 1s - loss: 0.1426 - categorical_accuracy: 0.9588 - val_loss: 0.1726 - val_categorical_accuracy: 0.9482 - 870ms/epoch - 6ms/step
Epoch 233/250
141/141 - 1s - loss: 0.0724 - categorical_accuracy: 0.9755 - val_loss: 0.1606 - val_categorical_accuracy: 0.9559 - 860ms/epoch - 6ms/step
Epoch 234/250
141/141 - 1s - loss: 0.0706 - categorical_accuracy: 0.9759 - val_loss: 0.1574 - val_categorical_accuracy: 0.9555 - 870ms/epoch - 6ms/step
Epoch 235/250
141/141 - 1s - loss: 0.1025 - categorical_accuracy: 0.9681 - val_loss: 0.1721 - val_categorical_accuracy: 0.9475 - 860ms/epoch - 6ms/step
Epoch 236/250
141/141 - 1s - loss: 0.0716 - categorical_accuracy: 0.9757 - val_loss: 0.2552 - val_categorical_accuracy: 0.9287 - 850ms/epoch - 6ms/step
Epoch 237/250
141/141 - 1s - loss: 0.0822 - categorical_accuracy: 0.9721 - val_loss: 0.1630 - val_categorical_accuracy: 0.9534 - 880ms/epoch - 6ms/step
Epoch 238/250
141/141 - 1s - loss: 0.0754 - categorical_accuracy: 0.9745 - val_loss: 0.1562 - val_categorical_accuracy: 0.9568 - 860ms/epoch - 6ms/step
Epoch 239/250
141/141 - 1s - loss: 0.0710 - categorical_accuracy: 0.9758 - val_loss: 0.1545 - val_categorical_accuracy: 0.9568 - 850ms/epoch - 6ms/step
Epoch 240/250
141/141 - 1s - loss: 0.0695 - categorical_accuracy: 0.9762 - val_loss: 0.1581 - val_categorical_accuracy: 0.9566 - 860ms/epoch - 6ms/step
Epoch 241/250
141/141 - 1s - loss: 0.0672 - categorical_accuracy: 0.9770 - val_loss: 0.3089 - val_categorical_accuracy: 0.9217 - 870ms/epoch - 6ms/step
Epoch 242/250
141/141 - 1s - loss: 0.0979 - categorical_accuracy: 0.9681 - val_loss: 0.1615 - val_categorical_accuracy: 0.9539 - 870ms/epoch - 6ms/step
Epoch 243/250
141/141 - 1s - loss: 0.1277 - categorical_accuracy: 0.9624 - val_loss: 0.1639 - val_categorical_accuracy: 0.9514 - 860ms/epoch - 6ms/step
Epoch 244/250
141/141 - 1s - loss: 0.0675 - categorical_accuracy: 0.9771 - val_loss: 0.1776 - val_categorical_accuracy: 0.9455 - 860ms/epoch - 6ms/step
Epoch 245/250
141/141 - 1s - loss: 0.0700 - categorical_accuracy: 0.9762 - val_loss: 0.1683 - val_categorical_accuracy: 0.9552 - 860ms/epoch - 6ms/step
Epoch 246/250
141/141 - 1s - loss: 0.0684 - categorical_accuracy: 0.9767 - val_loss: 0.1651 - val_categorical_accuracy: 0.9550 - 860ms/epoch - 6ms/step
Epoch 247/250
141/141 - 1s - loss: 0.0683 - categorical_accuracy: 0.9762 - val_loss: 0.1579 - val_categorical_accuracy: 0.9546 - 860ms/epoch - 6ms/step
Epoch 248/250
141/141 - 1s - loss: 0.0678 - categorical_accuracy: 0.9767 - val_loss: 0.1971 - val_categorical_accuracy: 0.9423 - 860ms/epoch - 6ms/step
Epoch 249/250
141/141 - 1s - loss: 0.0693 - categorical_accuracy: 0.9762 - val_loss: 0.1852 - val_categorical_accuracy: 0.9488 - 850ms/epoch - 6ms/step
Epoch 250/250
141/141 - 1s - loss: 0.1665 - categorical_accuracy: 0.9529 - val_loss: 0.1622 - val_categorical_accuracy: 0.9542 - 860ms/epoch - 6ms/step
processing fold # 9 
Epoch 1/250
141/141 - 2s - loss: 1.9373 - categorical_accuracy: 0.2527 - val_loss: 1.9942 - val_categorical_accuracy: 0.2554 - 2s/epoch - 12ms/step
Epoch 2/250
141/141 - 1s - loss: 1.5924 - categorical_accuracy: 0.3992 - val_loss: 1.3459 - val_categorical_accuracy: 0.4973 - 850ms/epoch - 6ms/step
Epoch 3/250
141/141 - 1s - loss: 1.3207 - categorical_accuracy: 0.5039 - val_loss: 1.2183 - val_categorical_accuracy: 0.5407 - 860ms/epoch - 6ms/step
Epoch 4/250
141/141 - 1s - loss: 1.1590 - categorical_accuracy: 0.5660 - val_loss: 0.9988 - val_categorical_accuracy: 0.6149 - 860ms/epoch - 6ms/step
Epoch 5/250
141/141 - 1s - loss: 1.0061 - categorical_accuracy: 0.6233 - val_loss: 0.9076 - val_categorical_accuracy: 0.6551 - 860ms/epoch - 6ms/step
Epoch 6/250
141/141 - 1s - loss: 1.1670 - categorical_accuracy: 0.5788 - val_loss: 0.8964 - val_categorical_accuracy: 0.6619 - 860ms/epoch - 6ms/step
Epoch 7/250
141/141 - 1s - loss: 0.8835 - categorical_accuracy: 0.6768 - val_loss: 0.7330 - val_categorical_accuracy: 0.7289 - 860ms/epoch - 6ms/step
Epoch 8/250
141/141 - 1s - loss: 0.7541 - categorical_accuracy: 0.7184 - val_loss: 0.7039 - val_categorical_accuracy: 0.7325 - 850ms/epoch - 6ms/step
Epoch 9/250
141/141 - 1s - loss: 0.8226 - categorical_accuracy: 0.7083 - val_loss: 0.7679 - val_categorical_accuracy: 0.7020 - 850ms/epoch - 6ms/step
Epoch 10/250
141/141 - 1s - loss: 0.6688 - categorical_accuracy: 0.7501 - val_loss: 0.6188 - val_categorical_accuracy: 0.7716 - 860ms/epoch - 6ms/step
Epoch 11/250
141/141 - 1s - loss: 0.6222 - categorical_accuracy: 0.7678 - val_loss: 0.5744 - val_categorical_accuracy: 0.7903 - 860ms/epoch - 6ms/step
Epoch 12/250
141/141 - 1s - loss: 0.7731 - categorical_accuracy: 0.7292 - val_loss: 0.5731 - val_categorical_accuracy: 0.7923 - 860ms/epoch - 6ms/step
Epoch 13/250
141/141 - 1s - loss: 0.5798 - categorical_accuracy: 0.7860 - val_loss: 0.5179 - val_categorical_accuracy: 0.8105 - 860ms/epoch - 6ms/step
Epoch 14/250
141/141 - 1s - loss: 0.6013 - categorical_accuracy: 0.7837 - val_loss: 0.6041 - val_categorical_accuracy: 0.7773 - 860ms/epoch - 6ms/step
Epoch 15/250
141/141 - 1s - loss: 0.5850 - categorical_accuracy: 0.7926 - val_loss: 0.5172 - val_categorical_accuracy: 0.8112 - 850ms/epoch - 6ms/step
Epoch 16/250
141/141 - 1s - loss: 0.4977 - categorical_accuracy: 0.8139 - val_loss: 0.5297 - val_categorical_accuracy: 0.8024 - 860ms/epoch - 6ms/step
Epoch 17/250
141/141 - 1s - loss: 0.6160 - categorical_accuracy: 0.7883 - val_loss: 0.4969 - val_categorical_accuracy: 0.8199 - 850ms/epoch - 6ms/step
Epoch 18/250
141/141 - 1s - loss: 0.4613 - categorical_accuracy: 0.8292 - val_loss: 0.4986 - val_categorical_accuracy: 0.8170 - 860ms/epoch - 6ms/step
Epoch 19/250
141/141 - 1s - loss: 0.4417 - categorical_accuracy: 0.8359 - val_loss: 0.4750 - val_categorical_accuracy: 0.8294 - 860ms/epoch - 6ms/step
Epoch 20/250
141/141 - 1s - loss: 0.4453 - categorical_accuracy: 0.8381 - val_loss: 0.4295 - val_categorical_accuracy: 0.8376 - 890ms/epoch - 6ms/step
Epoch 21/250
141/141 - 1s - loss: 0.4519 - categorical_accuracy: 0.8398 - val_loss: 0.4059 - val_categorical_accuracy: 0.8496 - 850ms/epoch - 6ms/step
Epoch 22/250
141/141 - 1s - loss: 0.3923 - categorical_accuracy: 0.8555 - val_loss: 0.4064 - val_categorical_accuracy: 0.8482 - 880ms/epoch - 6ms/step
Epoch 23/250
141/141 - 1s - loss: 0.3950 - categorical_accuracy: 0.8569 - val_loss: 0.4617 - val_categorical_accuracy: 0.8221 - 860ms/epoch - 6ms/step
Epoch 24/250
141/141 - 1s - loss: 0.3887 - categorical_accuracy: 0.8589 - val_loss: 0.4069 - val_categorical_accuracy: 0.8475 - 850ms/epoch - 6ms/step
Epoch 25/250
141/141 - 1s - loss: 0.3671 - categorical_accuracy: 0.8669 - val_loss: 0.4756 - val_categorical_accuracy: 0.8202 - 860ms/epoch - 6ms/step
Epoch 26/250
141/141 - 1s - loss: 0.3535 - categorical_accuracy: 0.8712 - val_loss: 0.4156 - val_categorical_accuracy: 0.8474 - 850ms/epoch - 6ms/step
Epoch 27/250
141/141 - 1s - loss: 0.3425 - categorical_accuracy: 0.8755 - val_loss: 0.3783 - val_categorical_accuracy: 0.8601 - 870ms/epoch - 6ms/step
Epoch 28/250
141/141 - 1s - loss: 0.4311 - categorical_accuracy: 0.8534 - val_loss: 0.3209 - val_categorical_accuracy: 0.8865 - 850ms/epoch - 6ms/step
Epoch 29/250
141/141 - 1s - loss: 0.3224 - categorical_accuracy: 0.8836 - val_loss: 0.3299 - val_categorical_accuracy: 0.8830 - 860ms/epoch - 6ms/step
Epoch 30/250
141/141 - 1s - loss: 0.3086 - categorical_accuracy: 0.8876 - val_loss: 0.3317 - val_categorical_accuracy: 0.8813 - 1s/epoch - 7ms/step
Epoch 31/250
141/141 - 1s - loss: 0.3363 - categorical_accuracy: 0.8812 - val_loss: 0.3238 - val_categorical_accuracy: 0.8825 - 860ms/epoch - 6ms/step
Epoch 32/250
141/141 - 1s - loss: 0.3332 - categorical_accuracy: 0.8848 - val_loss: 0.3096 - val_categorical_accuracy: 0.8881 - 852ms/epoch - 6ms/step
Epoch 33/250
141/141 - 1s - loss: 0.2987 - categorical_accuracy: 0.8924 - val_loss: 0.3070 - val_categorical_accuracy: 0.8888 - 870ms/epoch - 6ms/step
Epoch 34/250
141/141 - 1s - loss: 0.3037 - categorical_accuracy: 0.8933 - val_loss: 0.2908 - val_categorical_accuracy: 0.8972 - 870ms/epoch - 6ms/step
Epoch 35/250
141/141 - 1s - loss: 0.2883 - categorical_accuracy: 0.8970 - val_loss: 0.2703 - val_categorical_accuracy: 0.9058 - 860ms/epoch - 6ms/step
Epoch 36/250
141/141 - 1s - loss: 0.3099 - categorical_accuracy: 0.8944 - val_loss: 0.2838 - val_categorical_accuracy: 0.9001 - 860ms/epoch - 6ms/step
Epoch 37/250
141/141 - 1s - loss: 0.2624 - categorical_accuracy: 0.9057 - val_loss: 0.3132 - val_categorical_accuracy: 0.8880 - 850ms/epoch - 6ms/step
Epoch 38/250
141/141 - 1s - loss: 0.2627 - categorical_accuracy: 0.9063 - val_loss: 0.2807 - val_categorical_accuracy: 0.9012 - 860ms/epoch - 6ms/step
Epoch 39/250
141/141 - 1s - loss: 0.2516 - categorical_accuracy: 0.9102 - val_loss: 0.4041 - val_categorical_accuracy: 0.8531 - 860ms/epoch - 6ms/step
Epoch 40/250
141/141 - 1s - loss: 0.2836 - categorical_accuracy: 0.9027 - val_loss: 0.3198 - val_categorical_accuracy: 0.8802 - 870ms/epoch - 6ms/step
Epoch 41/250
141/141 - 1s - loss: 0.3131 - categorical_accuracy: 0.8951 - val_loss: 0.2832 - val_categorical_accuracy: 0.9000 - 860ms/epoch - 6ms/step
Epoch 42/250
141/141 - 1s - loss: 0.2287 - categorical_accuracy: 0.9201 - val_loss: 0.2736 - val_categorical_accuracy: 0.9032 - 850ms/epoch - 6ms/step
Epoch 43/250
141/141 - 1s - loss: 0.2406 - categorical_accuracy: 0.9148 - val_loss: 0.2924 - val_categorical_accuracy: 0.8959 - 860ms/epoch - 6ms/step
Epoch 44/250
141/141 - 1s - loss: 0.2519 - categorical_accuracy: 0.9126 - val_loss: 0.2377 - val_categorical_accuracy: 0.9179 - 860ms/epoch - 6ms/step
Epoch 45/250
141/141 - 1s - loss: 0.2646 - categorical_accuracy: 0.9097 - val_loss: 0.2701 - val_categorical_accuracy: 0.9061 - 850ms/epoch - 6ms/step
Epoch 46/250
141/141 - 1s - loss: 0.2367 - categorical_accuracy: 0.9187 - val_loss: 0.2351 - val_categorical_accuracy: 0.9184 - 850ms/epoch - 6ms/step
Epoch 47/250
141/141 - 1s - loss: 0.2155 - categorical_accuracy: 0.9244 - val_loss: 0.2323 - val_categorical_accuracy: 0.9193 - 860ms/epoch - 6ms/step
Epoch 48/250
141/141 - 1s - loss: 0.2134 - categorical_accuracy: 0.9248 - val_loss: 0.2954 - val_categorical_accuracy: 0.8853 - 850ms/epoch - 6ms/step
Epoch 49/250
141/141 - 1s - loss: 0.2164 - categorical_accuracy: 0.9237 - val_loss: 0.2826 - val_categorical_accuracy: 0.9011 - 850ms/epoch - 6ms/step
Epoch 50/250
141/141 - 1s - loss: 0.2154 - categorical_accuracy: 0.9241 - val_loss: 0.2556 - val_categorical_accuracy: 0.9078 - 860ms/epoch - 6ms/step
Epoch 51/250
141/141 - 1s - loss: 0.2051 - categorical_accuracy: 0.9278 - val_loss: 0.2665 - val_categorical_accuracy: 0.9067 - 860ms/epoch - 6ms/step
Epoch 52/250
141/141 - 1s - loss: 0.2204 - categorical_accuracy: 0.9228 - val_loss: 0.2129 - val_categorical_accuracy: 0.9264 - 870ms/epoch - 6ms/step
Epoch 53/250
141/141 - 1s - loss: 0.2017 - categorical_accuracy: 0.9293 - val_loss: 0.2430 - val_categorical_accuracy: 0.9155 - 870ms/epoch - 6ms/step
Epoch 54/250
141/141 - 1s - loss: 0.1952 - categorical_accuracy: 0.9316 - val_loss: 0.3161 - val_categorical_accuracy: 0.8873 - 870ms/epoch - 6ms/step
Epoch 55/250
141/141 - 1s - loss: 0.1981 - categorical_accuracy: 0.9307 - val_loss: 0.2404 - val_categorical_accuracy: 0.9176 - 860ms/epoch - 6ms/step
Epoch 56/250
141/141 - 1s - loss: 0.2656 - categorical_accuracy: 0.9156 - val_loss: 0.2221 - val_categorical_accuracy: 0.9230 - 860ms/epoch - 6ms/step
Epoch 57/250
141/141 - 1s - loss: 0.1813 - categorical_accuracy: 0.9369 - val_loss: 0.2449 - val_categorical_accuracy: 0.9166 - 860ms/epoch - 6ms/step
Epoch 58/250
141/141 - 1s - loss: 0.1906 - categorical_accuracy: 0.9339 - val_loss: 2.2252 - val_categorical_accuracy: 0.6699 - 860ms/epoch - 6ms/step
Epoch 59/250
141/141 - 1s - loss: 0.2657 - categorical_accuracy: 0.9176 - val_loss: 0.2015 - val_categorical_accuracy: 0.9305 - 870ms/epoch - 6ms/step
Epoch 60/250
141/141 - 1s - loss: 0.1856 - categorical_accuracy: 0.9358 - val_loss: 0.2487 - val_categorical_accuracy: 0.9130 - 880ms/epoch - 6ms/step
Epoch 61/250
141/141 - 1s - loss: 0.1738 - categorical_accuracy: 0.9392 - val_loss: 0.2079 - val_categorical_accuracy: 0.9280 - 870ms/epoch - 6ms/step
Epoch 62/250
141/141 - 1s - loss: 0.1945 - categorical_accuracy: 0.9343 - val_loss: 0.2237 - val_categorical_accuracy: 0.9228 - 880ms/epoch - 6ms/step
Epoch 63/250
141/141 - 1s - loss: 0.1918 - categorical_accuracy: 0.9341 - val_loss: 0.2077 - val_categorical_accuracy: 0.9304 - 870ms/epoch - 6ms/step
Epoch 64/250
141/141 - 1s - loss: 0.1740 - categorical_accuracy: 0.9399 - val_loss: 0.2177 - val_categorical_accuracy: 0.9215 - 860ms/epoch - 6ms/step
Epoch 65/250
141/141 - 1s - loss: 0.1642 - categorical_accuracy: 0.9426 - val_loss: 0.3847 - val_categorical_accuracy: 0.8661 - 850ms/epoch - 6ms/step
Epoch 66/250
141/141 - 1s - loss: 0.1947 - categorical_accuracy: 0.9344 - val_loss: 0.2141 - val_categorical_accuracy: 0.9257 - 870ms/epoch - 6ms/step
Epoch 67/250
141/141 - 1s - loss: 0.1820 - categorical_accuracy: 0.9388 - val_loss: 0.2030 - val_categorical_accuracy: 0.9274 - 860ms/epoch - 6ms/step
Epoch 68/250
141/141 - 1s - loss: 0.1670 - categorical_accuracy: 0.9421 - val_loss: 0.2004 - val_categorical_accuracy: 0.9327 - 860ms/epoch - 6ms/step
Epoch 69/250
141/141 - 1s - loss: 0.1679 - categorical_accuracy: 0.9426 - val_loss: 0.1843 - val_categorical_accuracy: 0.9372 - 870ms/epoch - 6ms/step
Epoch 70/250
141/141 - 1s - loss: 0.1588 - categorical_accuracy: 0.9442 - val_loss: 0.2454 - val_categorical_accuracy: 0.9141 - 850ms/epoch - 6ms/step
Epoch 71/250
141/141 - 1s - loss: 0.1601 - categorical_accuracy: 0.9443 - val_loss: 0.2470 - val_categorical_accuracy: 0.9160 - 850ms/epoch - 6ms/step
Epoch 72/250
141/141 - 1s - loss: 0.2102 - categorical_accuracy: 0.9337 - val_loss: 0.1843 - val_categorical_accuracy: 0.9376 - 860ms/epoch - 6ms/step
Epoch 73/250
141/141 - 1s - loss: 0.1496 - categorical_accuracy: 0.9482 - val_loss: 0.1903 - val_categorical_accuracy: 0.9340 - 860ms/epoch - 6ms/step
Epoch 74/250
141/141 - 1s - loss: 0.1499 - categorical_accuracy: 0.9479 - val_loss: 0.2046 - val_categorical_accuracy: 0.9286 - 870ms/epoch - 6ms/step
Epoch 75/250
141/141 - 1s - loss: 0.1653 - categorical_accuracy: 0.9435 - val_loss: 0.2029 - val_categorical_accuracy: 0.9309 - 860ms/epoch - 6ms/step
Epoch 76/250
141/141 - 1s - loss: 0.1548 - categorical_accuracy: 0.9467 - val_loss: 0.2681 - val_categorical_accuracy: 0.9132 - 860ms/epoch - 6ms/step
Epoch 77/250
141/141 - 1s - loss: 0.2567 - categorical_accuracy: 0.9236 - val_loss: 0.2340 - val_categorical_accuracy: 0.9208 - 850ms/epoch - 6ms/step
Epoch 78/250
141/141 - 1s - loss: 0.1462 - categorical_accuracy: 0.9504 - val_loss: 0.1763 - val_categorical_accuracy: 0.9403 - 860ms/epoch - 6ms/step
Epoch 79/250
141/141 - 1s - loss: 0.1524 - categorical_accuracy: 0.9477 - val_loss: 0.1869 - val_categorical_accuracy: 0.9363 - 850ms/epoch - 6ms/step
Epoch 80/250
141/141 - 1s - loss: 0.1422 - categorical_accuracy: 0.9514 - val_loss: 0.1972 - val_categorical_accuracy: 0.9331 - 870ms/epoch - 6ms/step
Epoch 81/250
141/141 - 1s - loss: 0.1532 - categorical_accuracy: 0.9481 - val_loss: 0.2076 - val_categorical_accuracy: 0.9299 - 850ms/epoch - 6ms/step
Epoch 82/250
141/141 - 1s - loss: 0.1924 - categorical_accuracy: 0.9448 - val_loss: 3.9214 - val_categorical_accuracy: 0.4642 - 860ms/epoch - 6ms/step
Epoch 83/250
141/141 - 1s - loss: 0.4437 - categorical_accuracy: 0.8614 - val_loss: 0.2094 - val_categorical_accuracy: 0.9291 - 860ms/epoch - 6ms/step
Epoch 84/250
141/141 - 1s - loss: 0.1530 - categorical_accuracy: 0.9478 - val_loss: 0.1831 - val_categorical_accuracy: 0.9375 - 870ms/epoch - 6ms/step
Epoch 85/250
141/141 - 1s - loss: 0.1406 - categorical_accuracy: 0.9515 - val_loss: 0.1801 - val_categorical_accuracy: 0.9399 - 860ms/epoch - 6ms/step
Epoch 86/250
141/141 - 1s - loss: 0.1447 - categorical_accuracy: 0.9498 - val_loss: 0.1920 - val_categorical_accuracy: 0.9340 - 870ms/epoch - 6ms/step
Epoch 87/250
141/141 - 1s - loss: 0.1351 - categorical_accuracy: 0.9531 - val_loss: 0.1831 - val_categorical_accuracy: 0.9362 - 860ms/epoch - 6ms/step
Epoch 88/250
141/141 - 1s - loss: 0.1485 - categorical_accuracy: 0.9493 - val_loss: 0.1714 - val_categorical_accuracy: 0.9436 - 860ms/epoch - 6ms/step
Epoch 89/250
141/141 - 1s - loss: 0.1279 - categorical_accuracy: 0.9559 - val_loss: 0.2844 - val_categorical_accuracy: 0.9090 - 860ms/epoch - 6ms/step
Epoch 90/250
141/141 - 1s - loss: 0.1539 - categorical_accuracy: 0.9495 - val_loss: 0.1859 - val_categorical_accuracy: 0.9355 - 860ms/epoch - 6ms/step
Epoch 91/250
141/141 - 1s - loss: 0.1341 - categorical_accuracy: 0.9541 - val_loss: 0.1871 - val_categorical_accuracy: 0.9370 - 860ms/epoch - 6ms/step
Epoch 92/250
141/141 - 1s - loss: 0.1316 - categorical_accuracy: 0.9546 - val_loss: 0.1728 - val_categorical_accuracy: 0.9423 - 860ms/epoch - 6ms/step
Epoch 93/250
141/141 - 1s - loss: 0.1227 - categorical_accuracy: 0.9576 - val_loss: 0.1842 - val_categorical_accuracy: 0.9369 - 850ms/epoch - 6ms/step
Epoch 94/250
141/141 - 1s - loss: 0.1435 - categorical_accuracy: 0.9526 - val_loss: 0.1741 - val_categorical_accuracy: 0.9427 - 850ms/epoch - 6ms/step
Epoch 95/250
141/141 - 1s - loss: 0.1182 - categorical_accuracy: 0.9596 - val_loss: 0.1773 - val_categorical_accuracy: 0.9399 - 860ms/epoch - 6ms/step
Epoch 96/250
141/141 - 1s - loss: 0.1311 - categorical_accuracy: 0.9550 - val_loss: 0.1890 - val_categorical_accuracy: 0.9363 - 870ms/epoch - 6ms/step
Epoch 97/250
141/141 - 1s - loss: 0.1320 - categorical_accuracy: 0.9549 - val_loss: 0.1691 - val_categorical_accuracy: 0.9436 - 870ms/epoch - 6ms/step
Epoch 98/250
141/141 - 1s - loss: 0.1668 - categorical_accuracy: 0.9475 - val_loss: 0.1678 - val_categorical_accuracy: 0.9431 - 870ms/epoch - 6ms/step
Epoch 99/250
141/141 - 1s - loss: 0.1169 - categorical_accuracy: 0.9596 - val_loss: 0.1862 - val_categorical_accuracy: 0.9369 - 860ms/epoch - 6ms/step
Epoch 100/250
141/141 - 1s - loss: 0.1421 - categorical_accuracy: 0.9535 - val_loss: 0.2043 - val_categorical_accuracy: 0.9301 - 860ms/epoch - 6ms/step
Epoch 101/250
141/141 - 1s - loss: 0.1186 - categorical_accuracy: 0.9594 - val_loss: 0.1696 - val_categorical_accuracy: 0.9422 - 860ms/epoch - 6ms/step
Epoch 102/250
141/141 - 1s - loss: 0.1214 - categorical_accuracy: 0.9583 - val_loss: 0.1619 - val_categorical_accuracy: 0.9450 - 866ms/epoch - 6ms/step
Epoch 103/250
141/141 - 1s - loss: 0.1237 - categorical_accuracy: 0.9580 - val_loss: 0.1928 - val_categorical_accuracy: 0.9339 - 850ms/epoch - 6ms/step
Epoch 104/250
141/141 - 1s - loss: 0.1256 - categorical_accuracy: 0.9579 - val_loss: 0.1734 - val_categorical_accuracy: 0.9435 - 860ms/epoch - 6ms/step
Epoch 105/250
141/141 - 1s - loss: 0.1408 - categorical_accuracy: 0.9529 - val_loss: 0.1722 - val_categorical_accuracy: 0.9430 - 850ms/epoch - 6ms/step
Epoch 106/250
141/141 - 1s - loss: 0.1312 - categorical_accuracy: 0.9572 - val_loss: 0.1764 - val_categorical_accuracy: 0.9416 - 860ms/epoch - 6ms/step
Epoch 107/250
141/141 - 1s - loss: 0.1082 - categorical_accuracy: 0.9636 - val_loss: 0.1597 - val_categorical_accuracy: 0.9469 - 860ms/epoch - 6ms/step
Epoch 108/250
141/141 - 1s - loss: 0.1083 - categorical_accuracy: 0.9629 - val_loss: 0.1815 - val_categorical_accuracy: 0.9409 - 860ms/epoch - 6ms/step
Epoch 109/250
141/141 - 1s - loss: 0.2074 - categorical_accuracy: 0.9391 - val_loss: 0.1714 - val_categorical_accuracy: 0.9422 - 860ms/epoch - 6ms/step
Epoch 110/250
141/141 - 1s - loss: 0.1079 - categorical_accuracy: 0.9636 - val_loss: 0.2203 - val_categorical_accuracy: 0.9312 - 870ms/epoch - 6ms/step
Epoch 111/250
141/141 - 1s - loss: 0.1194 - categorical_accuracy: 0.9592 - val_loss: 0.1853 - val_categorical_accuracy: 0.9354 - 870ms/epoch - 6ms/step
Epoch 112/250
141/141 - 1s - loss: 0.1109 - categorical_accuracy: 0.9620 - val_loss: 0.1924 - val_categorical_accuracy: 0.9358 - 860ms/epoch - 6ms/step
Epoch 113/250
141/141 - 1s - loss: 0.1039 - categorical_accuracy: 0.9646 - val_loss: 0.1808 - val_categorical_accuracy: 0.9427 - 860ms/epoch - 6ms/step
Epoch 114/250
141/141 - 1s - loss: 0.1126 - categorical_accuracy: 0.9614 - val_loss: 0.2595 - val_categorical_accuracy: 0.9210 - 860ms/epoch - 6ms/step
Epoch 115/250
141/141 - 1s - loss: 0.2115 - categorical_accuracy: 0.9383 - val_loss: 0.1940 - val_categorical_accuracy: 0.9335 - 860ms/epoch - 6ms/step
Epoch 116/250
141/141 - 1s - loss: 0.1064 - categorical_accuracy: 0.9644 - val_loss: 0.1736 - val_categorical_accuracy: 0.9446 - 850ms/epoch - 6ms/step
Epoch 117/250
141/141 - 1s - loss: 0.1037 - categorical_accuracy: 0.9644 - val_loss: 0.1733 - val_categorical_accuracy: 0.9426 - 850ms/epoch - 6ms/step
Epoch 118/250
141/141 - 1s - loss: 0.1083 - categorical_accuracy: 0.9628 - val_loss: 0.1725 - val_categorical_accuracy: 0.9445 - 850ms/epoch - 6ms/step
Epoch 119/250
141/141 - 1s - loss: 0.1437 - categorical_accuracy: 0.9553 - val_loss: 0.1564 - val_categorical_accuracy: 0.9492 - 870ms/epoch - 6ms/step
Epoch 120/250
141/141 - 1s - loss: 0.1102 - categorical_accuracy: 0.9624 - val_loss: 0.1649 - val_categorical_accuracy: 0.9462 - 850ms/epoch - 6ms/step
Epoch 121/250
141/141 - 1s - loss: 0.1006 - categorical_accuracy: 0.9658 - val_loss: 0.1660 - val_categorical_accuracy: 0.9464 - 860ms/epoch - 6ms/step
Epoch 122/250
141/141 - 1s - loss: 0.1031 - categorical_accuracy: 0.9643 - val_loss: 0.1561 - val_categorical_accuracy: 0.9499 - 870ms/epoch - 6ms/step
Epoch 123/250
141/141 - 1s - loss: 0.0970 - categorical_accuracy: 0.9669 - val_loss: 0.1645 - val_categorical_accuracy: 0.9463 - 860ms/epoch - 6ms/step
Epoch 124/250
141/141 - 1s - loss: 0.1236 - categorical_accuracy: 0.9596 - val_loss: 0.1617 - val_categorical_accuracy: 0.9466 - 860ms/epoch - 6ms/step
Epoch 125/250
141/141 - 1s - loss: 0.1010 - categorical_accuracy: 0.9656 - val_loss: 0.1730 - val_categorical_accuracy: 0.9431 - 860ms/epoch - 6ms/step
Epoch 126/250
141/141 - 1s - loss: 0.1165 - categorical_accuracy: 0.9611 - val_loss: 0.1523 - val_categorical_accuracy: 0.9516 - 870ms/epoch - 6ms/step
Epoch 127/250
141/141 - 1s - loss: 0.1079 - categorical_accuracy: 0.9642 - val_loss: 0.1801 - val_categorical_accuracy: 0.9433 - 860ms/epoch - 6ms/step
Epoch 128/250
141/141 - 1s - loss: 0.1006 - categorical_accuracy: 0.9660 - val_loss: 0.1661 - val_categorical_accuracy: 0.9466 - 860ms/epoch - 6ms/step
Epoch 129/250
141/141 - 1s - loss: 0.1039 - categorical_accuracy: 0.9651 - val_loss: 0.1758 - val_categorical_accuracy: 0.9431 - 860ms/epoch - 6ms/step
Epoch 130/250
141/141 - 1s - loss: 0.1013 - categorical_accuracy: 0.9652 - val_loss: 0.1584 - val_categorical_accuracy: 0.9494 - 880ms/epoch - 6ms/step
Epoch 131/250
141/141 - 1s - loss: 0.1014 - categorical_accuracy: 0.9655 - val_loss: 0.1680 - val_categorical_accuracy: 0.9470 - 880ms/epoch - 6ms/step
Epoch 132/250
141/141 - 1s - loss: 0.1216 - categorical_accuracy: 0.9609 - val_loss: 0.1657 - val_categorical_accuracy: 0.9461 - 860ms/epoch - 6ms/step
Epoch 133/250
141/141 - 1s - loss: 0.0892 - categorical_accuracy: 0.9694 - val_loss: 0.1689 - val_categorical_accuracy: 0.9456 - 860ms/epoch - 6ms/step
Epoch 134/250
141/141 - 1s - loss: 0.0992 - categorical_accuracy: 0.9666 - val_loss: 0.1647 - val_categorical_accuracy: 0.9474 - 860ms/epoch - 6ms/step
Epoch 135/250
141/141 - 1s - loss: 0.1088 - categorical_accuracy: 0.9641 - val_loss: 0.1638 - val_categorical_accuracy: 0.9454 - 860ms/epoch - 6ms/step
Epoch 136/250
141/141 - 1s - loss: 0.0948 - categorical_accuracy: 0.9678 - val_loss: 0.1884 - val_categorical_accuracy: 0.9385 - 860ms/epoch - 6ms/step
Epoch 137/250
141/141 - 1s - loss: 0.1341 - categorical_accuracy: 0.9576 - val_loss: 0.1592 - val_categorical_accuracy: 0.9490 - 860ms/epoch - 6ms/step
Epoch 138/250
141/141 - 1s - loss: 0.0918 - categorical_accuracy: 0.9687 - val_loss: 0.1776 - val_categorical_accuracy: 0.9452 - 860ms/epoch - 6ms/step
Epoch 139/250
141/141 - 1s - loss: 0.1033 - categorical_accuracy: 0.9649 - val_loss: 0.1739 - val_categorical_accuracy: 0.9448 - 860ms/epoch - 6ms/step
Epoch 140/250
141/141 - 1s - loss: 0.1209 - categorical_accuracy: 0.9610 - val_loss: 0.1580 - val_categorical_accuracy: 0.9504 - 870ms/epoch - 6ms/step
Epoch 141/250
141/141 - 1s - loss: 0.0862 - categorical_accuracy: 0.9711 - val_loss: 0.1645 - val_categorical_accuracy: 0.9480 - 870ms/epoch - 6ms/step
Epoch 142/250
141/141 - 1s - loss: 0.1122 - categorical_accuracy: 0.9621 - val_loss: 0.1520 - val_categorical_accuracy: 0.9508 - 870ms/epoch - 6ms/step
Epoch 143/250
141/141 - 1s - loss: 0.0840 - categorical_accuracy: 0.9715 - val_loss: 0.1770 - val_categorical_accuracy: 0.9436 - 850ms/epoch - 6ms/step
Epoch 144/250
141/141 - 1s - loss: 0.1117 - categorical_accuracy: 0.9633 - val_loss: 0.1548 - val_categorical_accuracy: 0.9509 - 850ms/epoch - 6ms/step
Epoch 145/250
141/141 - 1s - loss: 0.1186 - categorical_accuracy: 0.9623 - val_loss: 0.1875 - val_categorical_accuracy: 0.9381 - 860ms/epoch - 6ms/step
Epoch 146/250
141/141 - 1s - loss: 0.0884 - categorical_accuracy: 0.9702 - val_loss: 0.1900 - val_categorical_accuracy: 0.9399 - 860ms/epoch - 6ms/step
Epoch 147/250
141/141 - 1s - loss: 0.0886 - categorical_accuracy: 0.9698 - val_loss: 0.1550 - val_categorical_accuracy: 0.9526 - 860ms/epoch - 6ms/step
Epoch 148/250
141/141 - 1s - loss: 0.0844 - categorical_accuracy: 0.9712 - val_loss: 0.2675 - val_categorical_accuracy: 0.9225 - 860ms/epoch - 6ms/step
Epoch 149/250
141/141 - 1s - loss: 0.1046 - categorical_accuracy: 0.9655 - val_loss: 0.1928 - val_categorical_accuracy: 0.9420 - 860ms/epoch - 6ms/step
Epoch 150/250
141/141 - 1s - loss: 0.1302 - categorical_accuracy: 0.9602 - val_loss: 0.1478 - val_categorical_accuracy: 0.9539 - 860ms/epoch - 6ms/step
Epoch 151/250
141/141 - 1s - loss: 0.0893 - categorical_accuracy: 0.9699 - val_loss: 0.1637 - val_categorical_accuracy: 0.9485 - 860ms/epoch - 6ms/step
Epoch 152/250
141/141 - 1s - loss: 0.0983 - categorical_accuracy: 0.9667 - val_loss: 0.1909 - val_categorical_accuracy: 0.9368 - 860ms/epoch - 6ms/step
Epoch 153/250
141/141 - 1s - loss: 0.0824 - categorical_accuracy: 0.9718 - val_loss: 0.1504 - val_categorical_accuracy: 0.9517 - 860ms/epoch - 6ms/step
Epoch 154/250
141/141 - 1s - loss: 0.1244 - categorical_accuracy: 0.9606 - val_loss: 0.1537 - val_categorical_accuracy: 0.9516 - 870ms/epoch - 6ms/step
Epoch 155/250
141/141 - 1s - loss: 0.0798 - categorical_accuracy: 0.9730 - val_loss: 0.1641 - val_categorical_accuracy: 0.9510 - 860ms/epoch - 6ms/step
Epoch 156/250
141/141 - 1s - loss: 0.0823 - categorical_accuracy: 0.9719 - val_loss: 0.1637 - val_categorical_accuracy: 0.9493 - 870ms/epoch - 6ms/step
Epoch 157/250
141/141 - 1s - loss: 0.1072 - categorical_accuracy: 0.9651 - val_loss: 0.1499 - val_categorical_accuracy: 0.9537 - 860ms/epoch - 6ms/step
Epoch 158/250
141/141 - 1s - loss: 0.0787 - categorical_accuracy: 0.9734 - val_loss: 0.2490 - val_categorical_accuracy: 0.9281 - 860ms/epoch - 6ms/step
Epoch 159/250
141/141 - 1s - loss: 0.0923 - categorical_accuracy: 0.9687 - val_loss: 0.2504 - val_categorical_accuracy: 0.9206 - 860ms/epoch - 6ms/step
Epoch 160/250
141/141 - 1s - loss: 0.0996 - categorical_accuracy: 0.9668 - val_loss: 0.1496 - val_categorical_accuracy: 0.9537 - 870ms/epoch - 6ms/step
Epoch 161/250
141/141 - 1s - loss: 0.1317 - categorical_accuracy: 0.9595 - val_loss: 0.1619 - val_categorical_accuracy: 0.9480 - 860ms/epoch - 6ms/step
Epoch 162/250
141/141 - 1s - loss: 0.0929 - categorical_accuracy: 0.9692 - val_loss: 0.1621 - val_categorical_accuracy: 0.9475 - 860ms/epoch - 6ms/step
Epoch 163/250
141/141 - 1s - loss: 0.0778 - categorical_accuracy: 0.9737 - val_loss: 0.1576 - val_categorical_accuracy: 0.9518 - 860ms/epoch - 6ms/step
Epoch 164/250
141/141 - 1s - loss: 0.1000 - categorical_accuracy: 0.9675 - val_loss: 0.1506 - val_categorical_accuracy: 0.9535 - 870ms/epoch - 6ms/step
Epoch 165/250
141/141 - 1s - loss: 0.0760 - categorical_accuracy: 0.9743 - val_loss: 0.1543 - val_categorical_accuracy: 0.9534 - 870ms/epoch - 6ms/step
Epoch 166/250
141/141 - 1s - loss: 0.0835 - categorical_accuracy: 0.9711 - val_loss: 0.3629 - val_categorical_accuracy: 0.8993 - 870ms/epoch - 6ms/step
Epoch 167/250
141/141 - 1s - loss: 0.0959 - categorical_accuracy: 0.9687 - val_loss: 0.1554 - val_categorical_accuracy: 0.9522 - 860ms/epoch - 6ms/step
Epoch 168/250
141/141 - 1s - loss: 0.0873 - categorical_accuracy: 0.9703 - val_loss: 0.1476 - val_categorical_accuracy: 0.9537 - 860ms/epoch - 6ms/step
Epoch 169/250
141/141 - 1s - loss: 0.0770 - categorical_accuracy: 0.9741 - val_loss: 0.1518 - val_categorical_accuracy: 0.9547 - 860ms/epoch - 6ms/step
Epoch 170/250
141/141 - 1s - loss: 0.0977 - categorical_accuracy: 0.9681 - val_loss: 0.1575 - val_categorical_accuracy: 0.9520 - 870ms/epoch - 6ms/step
Epoch 171/250
141/141 - 1s - loss: 0.0772 - categorical_accuracy: 0.9738 - val_loss: 0.2042 - val_categorical_accuracy: 0.9407 - 870ms/epoch - 6ms/step
Epoch 172/250
141/141 - 1s - loss: 0.1332 - categorical_accuracy: 0.9610 - val_loss: 0.1562 - val_categorical_accuracy: 0.9510 - 858ms/epoch - 6ms/step
Epoch 173/250
141/141 - 1s - loss: 0.0760 - categorical_accuracy: 0.9741 - val_loss: 0.1534 - val_categorical_accuracy: 0.9550 - 860ms/epoch - 6ms/step
Epoch 174/250
141/141 - 1s - loss: 0.0771 - categorical_accuracy: 0.9737 - val_loss: 0.1557 - val_categorical_accuracy: 0.9537 - 860ms/epoch - 6ms/step
Epoch 175/250
141/141 - 1s - loss: 0.0815 - categorical_accuracy: 0.9722 - val_loss: 0.2333 - val_categorical_accuracy: 0.9349 - 860ms/epoch - 6ms/step
Epoch 176/250
141/141 - 1s - loss: 0.1065 - categorical_accuracy: 0.9658 - val_loss: 0.1670 - val_categorical_accuracy: 0.9507 - 860ms/epoch - 6ms/step
Epoch 177/250
141/141 - 1s - loss: 0.1609 - categorical_accuracy: 0.9530 - val_loss: 0.1676 - val_categorical_accuracy: 0.9488 - 860ms/epoch - 6ms/step
Epoch 178/250
141/141 - 1s - loss: 0.0760 - categorical_accuracy: 0.9747 - val_loss: 0.1617 - val_categorical_accuracy: 0.9505 - 870ms/epoch - 6ms/step
Epoch 179/250
141/141 - 1s - loss: 0.0786 - categorical_accuracy: 0.9734 - val_loss: 0.1601 - val_categorical_accuracy: 0.9514 - 860ms/epoch - 6ms/step
Epoch 180/250
141/141 - 1s - loss: 0.1058 - categorical_accuracy: 0.9665 - val_loss: 0.1499 - val_categorical_accuracy: 0.9540 - 850ms/epoch - 6ms/step
Epoch 181/250
141/141 - 1s - loss: 0.0740 - categorical_accuracy: 0.9750 - val_loss: 0.1528 - val_categorical_accuracy: 0.9536 - 860ms/epoch - 6ms/step
Epoch 182/250
141/141 - 1s - loss: 0.0743 - categorical_accuracy: 0.9746 - val_loss: 0.2671 - val_categorical_accuracy: 0.9197 - 870ms/epoch - 6ms/step
Epoch 183/250
141/141 - 1s - loss: 0.0769 - categorical_accuracy: 0.9738 - val_loss: 0.1556 - val_categorical_accuracy: 0.9537 - 860ms/epoch - 6ms/step
Epoch 184/250
141/141 - 1s - loss: 0.0906 - categorical_accuracy: 0.9698 - val_loss: 0.1900 - val_categorical_accuracy: 0.9442 - 850ms/epoch - 6ms/step
Epoch 185/250
141/141 - 1s - loss: 0.0725 - categorical_accuracy: 0.9754 - val_loss: 0.1570 - val_categorical_accuracy: 0.9532 - 860ms/epoch - 6ms/step
Epoch 186/250
141/141 - 1s - loss: 0.0925 - categorical_accuracy: 0.9695 - val_loss: 0.1677 - val_categorical_accuracy: 0.9488 - 870ms/epoch - 6ms/step
Epoch 187/250
141/141 - 1s - loss: 0.0836 - categorical_accuracy: 0.9721 - val_loss: 0.1529 - val_categorical_accuracy: 0.9550 - 860ms/epoch - 6ms/step
Epoch 188/250
141/141 - 1s - loss: 0.0710 - categorical_accuracy: 0.9759 - val_loss: 0.1551 - val_categorical_accuracy: 0.9530 - 860ms/epoch - 6ms/step
Epoch 189/250
141/141 - 1s - loss: 0.0900 - categorical_accuracy: 0.9697 - val_loss: 0.1649 - val_categorical_accuracy: 0.9508 - 860ms/epoch - 6ms/step
Epoch 190/250
141/141 - 1s - loss: 0.0708 - categorical_accuracy: 0.9757 - val_loss: 0.1599 - val_categorical_accuracy: 0.9531 - 860ms/epoch - 6ms/step
Epoch 191/250
141/141 - 1s - loss: 0.0965 - categorical_accuracy: 0.9683 - val_loss: 0.1502 - val_categorical_accuracy: 0.9536 - 860ms/epoch - 6ms/step
Epoch 192/250
141/141 - 1s - loss: 0.0704 - categorical_accuracy: 0.9758 - val_loss: 0.1926 - val_categorical_accuracy: 0.9468 - 860ms/epoch - 6ms/step
Epoch 193/250
141/141 - 1s - loss: 0.0712 - categorical_accuracy: 0.9757 - val_loss: 0.1541 - val_categorical_accuracy: 0.9535 - 870ms/epoch - 6ms/step
Epoch 194/250
141/141 - 1s - loss: 0.1004 - categorical_accuracy: 0.9672 - val_loss: 0.1515 - val_categorical_accuracy: 0.9551 - 860ms/epoch - 6ms/step
Epoch 195/250
141/141 - 1s - loss: 0.0703 - categorical_accuracy: 0.9763 - val_loss: 0.1679 - val_categorical_accuracy: 0.9510 - 860ms/epoch - 6ms/step
Epoch 196/250
141/141 - 1s - loss: 0.0702 - categorical_accuracy: 0.9759 - val_loss: 0.1588 - val_categorical_accuracy: 0.9545 - 850ms/epoch - 6ms/step
Epoch 197/250
141/141 - 1s - loss: 0.0751 - categorical_accuracy: 0.9747 - val_loss: 0.1538 - val_categorical_accuracy: 0.9558 - 860ms/epoch - 6ms/step
Epoch 198/250
141/141 - 1s - loss: 0.0884 - categorical_accuracy: 0.9702 - val_loss: 0.1489 - val_categorical_accuracy: 0.9569 - 860ms/epoch - 6ms/step
Epoch 199/250
141/141 - 1s - loss: 0.0697 - categorical_accuracy: 0.9765 - val_loss: 0.1663 - val_categorical_accuracy: 0.9514 - 860ms/epoch - 6ms/step
Epoch 200/250
141/141 - 1s - loss: 0.0800 - categorical_accuracy: 0.9730 - val_loss: 0.2712 - val_categorical_accuracy: 0.9207 - 890ms/epoch - 6ms/step
Epoch 201/250
141/141 - 1s - loss: 0.0936 - categorical_accuracy: 0.9695 - val_loss: 0.1811 - val_categorical_accuracy: 0.9457 - 870ms/epoch - 6ms/step
Epoch 202/250
141/141 - 1s - loss: 0.1016 - categorical_accuracy: 0.9682 - val_loss: 0.1756 - val_categorical_accuracy: 0.9479 - 860ms/epoch - 6ms/step
Epoch 203/250
141/141 - 1s - loss: 0.0680 - categorical_accuracy: 0.9771 - val_loss: 0.1699 - val_categorical_accuracy: 0.9493 - 870ms/epoch - 6ms/step
Epoch 204/250
141/141 - 1s - loss: 0.0701 - categorical_accuracy: 0.9760 - val_loss: 0.1594 - val_categorical_accuracy: 0.9545 - 870ms/epoch - 6ms/step
Epoch 205/250
141/141 - 1s - loss: 0.0698 - categorical_accuracy: 0.9759 - val_loss: 0.1507 - val_categorical_accuracy: 0.9559 - 860ms/epoch - 6ms/step
Epoch 206/250
141/141 - 1s - loss: 0.0906 - categorical_accuracy: 0.9709 - val_loss: 0.1556 - val_categorical_accuracy: 0.9529 - 860ms/epoch - 6ms/step
Epoch 207/250
141/141 - 1s - loss: 0.0660 - categorical_accuracy: 0.9776 - val_loss: 0.1562 - val_categorical_accuracy: 0.9555 - 870ms/epoch - 6ms/step
Epoch 208/250
141/141 - 1s - loss: 0.0736 - categorical_accuracy: 0.9747 - val_loss: 0.1661 - val_categorical_accuracy: 0.9517 - 870ms/epoch - 6ms/step
Epoch 209/250
141/141 - 1s - loss: 0.0998 - categorical_accuracy: 0.9683 - val_loss: 0.1559 - val_categorical_accuracy: 0.9516 - 860ms/epoch - 6ms/step
Epoch 210/250
141/141 - 1s - loss: 0.1217 - categorical_accuracy: 0.9641 - val_loss: 0.1500 - val_categorical_accuracy: 0.9546 - 860ms/epoch - 6ms/step
Epoch 211/250
141/141 - 1s - loss: 0.0677 - categorical_accuracy: 0.9772 - val_loss: 0.1591 - val_categorical_accuracy: 0.9532 - 870ms/epoch - 6ms/step
Epoch 212/250
141/141 - 1s - loss: 0.0746 - categorical_accuracy: 0.9748 - val_loss: 0.1676 - val_categorical_accuracy: 0.9543 - 860ms/epoch - 6ms/step
Epoch 213/250
141/141 - 1s - loss: 0.0858 - categorical_accuracy: 0.9728 - val_loss: 0.1788 - val_categorical_accuracy: 0.9442 - 850ms/epoch - 6ms/step
Epoch 214/250
141/141 - 1s - loss: 0.0691 - categorical_accuracy: 0.9765 - val_loss: 0.1495 - val_categorical_accuracy: 0.9569 - 860ms/epoch - 6ms/step
Epoch 215/250
141/141 - 1s - loss: 0.0659 - categorical_accuracy: 0.9774 - val_loss: 0.1602 - val_categorical_accuracy: 0.9538 - 870ms/epoch - 6ms/step
Epoch 216/250
141/141 - 1s - loss: 0.0784 - categorical_accuracy: 0.9731 - val_loss: 0.1571 - val_categorical_accuracy: 0.9548 - 860ms/epoch - 6ms/step
Epoch 217/250
141/141 - 1s - loss: 0.0653 - categorical_accuracy: 0.9775 - val_loss: 0.1583 - val_categorical_accuracy: 0.9547 - 860ms/epoch - 6ms/step
Epoch 218/250
141/141 - 1s - loss: 0.0838 - categorical_accuracy: 0.9721 - val_loss: 0.1739 - val_categorical_accuracy: 0.9517 - 870ms/epoch - 6ms/step
Epoch 219/250
141/141 - 1s - loss: 0.0672 - categorical_accuracy: 0.9769 - val_loss: 0.1462 - val_categorical_accuracy: 0.9575 - 870ms/epoch - 6ms/step
Epoch 220/250
141/141 - 1s - loss: 0.0672 - categorical_accuracy: 0.9768 - val_loss: 0.1523 - val_categorical_accuracy: 0.9560 - 850ms/epoch - 6ms/step
Epoch 221/250
141/141 - 1s - loss: 0.0954 - categorical_accuracy: 0.9701 - val_loss: 0.1450 - val_categorical_accuracy: 0.9584 - 860ms/epoch - 6ms/step
Epoch 222/250
141/141 - 1s - loss: 0.0659 - categorical_accuracy: 0.9774 - val_loss: 0.1482 - val_categorical_accuracy: 0.9587 - 860ms/epoch - 6ms/step
Epoch 223/250
141/141 - 1s - loss: 0.0720 - categorical_accuracy: 0.9752 - val_loss: 0.1589 - val_categorical_accuracy: 0.9527 - 860ms/epoch - 6ms/step
Epoch 224/250
141/141 - 1s - loss: 0.0651 - categorical_accuracy: 0.9776 - val_loss: 0.3308 - val_categorical_accuracy: 0.9088 - 860ms/epoch - 6ms/step
Epoch 225/250
141/141 - 1s - loss: 0.0828 - categorical_accuracy: 0.9718 - val_loss: 0.1520 - val_categorical_accuracy: 0.9564 - 870ms/epoch - 6ms/step
Epoch 226/250
141/141 - 1s - loss: 0.0646 - categorical_accuracy: 0.9780 - val_loss: 0.1785 - val_categorical_accuracy: 0.9493 - 860ms/epoch - 6ms/step
Epoch 227/250
141/141 - 1s - loss: 0.0679 - categorical_accuracy: 0.9768 - val_loss: 0.1860 - val_categorical_accuracy: 0.9446 - 860ms/epoch - 6ms/step
Epoch 228/250
141/141 - 1s - loss: 0.0995 - categorical_accuracy: 0.9689 - val_loss: 0.1759 - val_categorical_accuracy: 0.9455 - 860ms/epoch - 6ms/step
Epoch 229/250
141/141 - 1s - loss: 0.0663 - categorical_accuracy: 0.9776 - val_loss: 0.1552 - val_categorical_accuracy: 0.9557 - 860ms/epoch - 6ms/step
Epoch 230/250
141/141 - 1s - loss: 0.0736 - categorical_accuracy: 0.9754 - val_loss: 0.1557 - val_categorical_accuracy: 0.9563 - 870ms/epoch - 6ms/step
Epoch 231/250
141/141 - 1s - loss: 0.1029 - categorical_accuracy: 0.9697 - val_loss: 0.2432 - val_categorical_accuracy: 0.9186 - 850ms/epoch - 6ms/step
Epoch 232/250
141/141 - 1s - loss: 0.0718 - categorical_accuracy: 0.9757 - val_loss: 0.1567 - val_categorical_accuracy: 0.9558 - 860ms/epoch - 6ms/step
Epoch 233/250
141/141 - 1s - loss: 0.0662 - categorical_accuracy: 0.9772 - val_loss: 0.1687 - val_categorical_accuracy: 0.9526 - 860ms/epoch - 6ms/step
Epoch 234/250
141/141 - 1s - loss: 0.0614 - categorical_accuracy: 0.9791 - val_loss: 0.1527 - val_categorical_accuracy: 0.9554 - 860ms/epoch - 6ms/step
Epoch 235/250
141/141 - 1s - loss: 0.0643 - categorical_accuracy: 0.9780 - val_loss: 0.1682 - val_categorical_accuracy: 0.9506 - 860ms/epoch - 6ms/step
Epoch 236/250
141/141 - 1s - loss: 0.0679 - categorical_accuracy: 0.9769 - val_loss: 0.1846 - val_categorical_accuracy: 0.9506 - 860ms/epoch - 6ms/step
Epoch 237/250
141/141 - 1s - loss: 0.0646 - categorical_accuracy: 0.9777 - val_loss: 0.1607 - val_categorical_accuracy: 0.9537 - 860ms/epoch - 6ms/step
Epoch 238/250
141/141 - 1s - loss: 0.0913 - categorical_accuracy: 0.9720 - val_loss: 0.1512 - val_categorical_accuracy: 0.9566 - 860ms/epoch - 6ms/step
Epoch 239/250
141/141 - 1s - loss: 0.0610 - categorical_accuracy: 0.9791 - val_loss: 0.1528 - val_categorical_accuracy: 0.9553 - 860ms/epoch - 6ms/step
Epoch 240/250
141/141 - 1s - loss: 0.0616 - categorical_accuracy: 0.9787 - val_loss: 0.1686 - val_categorical_accuracy: 0.9536 - 860ms/epoch - 6ms/step
Epoch 241/250
141/141 - 1s - loss: 0.0610 - categorical_accuracy: 0.9789 - val_loss: 0.1699 - val_categorical_accuracy: 0.9507 - 861ms/epoch - 6ms/step
Epoch 242/250
141/141 - 1s - loss: 0.0610 - categorical_accuracy: 0.9790 - val_loss: 0.1722 - val_categorical_accuracy: 0.9521 - 850ms/epoch - 6ms/step
Epoch 243/250
141/141 - 1s - loss: 0.0634 - categorical_accuracy: 0.9781 - val_loss: 0.1672 - val_categorical_accuracy: 0.9525 - 860ms/epoch - 6ms/step
Epoch 244/250
141/141 - 1s - loss: 0.1187 - categorical_accuracy: 0.9646 - val_loss: 0.1490 - val_categorical_accuracy: 0.9574 - 860ms/epoch - 6ms/step
Epoch 245/250
141/141 - 1s - loss: 0.0614 - categorical_accuracy: 0.9791 - val_loss: 0.1623 - val_categorical_accuracy: 0.9550 - 860ms/epoch - 6ms/step
Epoch 246/250
141/141 - 1s - loss: 0.0634 - categorical_accuracy: 0.9779 - val_loss: 0.1566 - val_categorical_accuracy: 0.9576 - 860ms/epoch - 6ms/step
Epoch 247/250
141/141 - 1s - loss: 0.0600 - categorical_accuracy: 0.9793 - val_loss: 0.1574 - val_categorical_accuracy: 0.9552 - 860ms/epoch - 6ms/step
Epoch 248/250
141/141 - 1s - loss: 0.0659 - categorical_accuracy: 0.9772 - val_loss: 0.2197 - val_categorical_accuracy: 0.9423 - 860ms/epoch - 6ms/step
Epoch 249/250
141/141 - 1s - loss: 0.0676 - categorical_accuracy: 0.9768 - val_loss: 0.1682 - val_categorical_accuracy: 0.9537 - 860ms/epoch - 6ms/step
Epoch 250/250
141/141 - 1s - loss: 0.0727 - categorical_accuracy: 0.9754 - val_loss: 0.1803 - val_categorical_accuracy: 0.9521 - 860ms/epoch - 6ms/step
processing fold # 10 
Epoch 1/250

WARNING:tensorflow:Callback method `on_train_batch_begin` is slow compared to the batch time (batch time: 0.0000s vs `on_train_batch_begin` time: 0.0017s). Check your callbacks.

141/141 - 2s - loss: 1.9577 - categorical_accuracy: 0.2577 - val_loss: 1.7059 - val_categorical_accuracy: 0.3683 - 2s/epoch - 12ms/step
Epoch 2/250
141/141 - 1s - loss: 1.5863 - categorical_accuracy: 0.3954 - val_loss: 1.4337 - val_categorical_accuracy: 0.4349 - 880ms/epoch - 6ms/step
Epoch 3/250
141/141 - 1s - loss: 1.3602 - categorical_accuracy: 0.4852 - val_loss: 1.3486 - val_categorical_accuracy: 0.4912 - 880ms/epoch - 6ms/step
Epoch 4/250
141/141 - 1s - loss: 1.1755 - categorical_accuracy: 0.5548 - val_loss: 1.1310 - val_categorical_accuracy: 0.5535 - 870ms/epoch - 6ms/step
Epoch 5/250
141/141 - 1s - loss: 1.1137 - categorical_accuracy: 0.5879 - val_loss: 1.0426 - val_categorical_accuracy: 0.6176 - 870ms/epoch - 6ms/step
Epoch 6/250
141/141 - 1s - loss: 0.9621 - categorical_accuracy: 0.6397 - val_loss: 0.9444 - val_categorical_accuracy: 0.6394 - 870ms/epoch - 6ms/step
Epoch 7/250
141/141 - 1s - loss: 0.8753 - categorical_accuracy: 0.6749 - val_loss: 1.5377 - val_categorical_accuracy: 0.5229 - 870ms/epoch - 6ms/step
Epoch 8/250
141/141 - 1s - loss: 0.8025 - categorical_accuracy: 0.7016 - val_loss: 0.8970 - val_categorical_accuracy: 0.6634 - 860ms/epoch - 6ms/step
Epoch 9/250
141/141 - 1s - loss: 1.2184 - categorical_accuracy: 0.5724 - val_loss: 1.3093 - val_categorical_accuracy: 0.5487 - 860ms/epoch - 6ms/step
Epoch 10/250
141/141 - 1s - loss: 1.0946 - categorical_accuracy: 0.6121 - val_loss: 0.8008 - val_categorical_accuracy: 0.7030 - 860ms/epoch - 6ms/step
Epoch 11/250
141/141 - 1s - loss: 0.7652 - categorical_accuracy: 0.7152 - val_loss: 0.7175 - val_categorical_accuracy: 0.7351 - 860ms/epoch - 6ms/step
Epoch 12/250
141/141 - 1s - loss: 0.6980 - categorical_accuracy: 0.7411 - val_loss: 0.5905 - val_categorical_accuracy: 0.7795 - 880ms/epoch - 6ms/step
Epoch 13/250
141/141 - 1s - loss: 0.6369 - categorical_accuracy: 0.7611 - val_loss: 0.6005 - val_categorical_accuracy: 0.7782 - 860ms/epoch - 6ms/step
Epoch 14/250
141/141 - 1s - loss: 0.6579 - categorical_accuracy: 0.7615 - val_loss: 0.5954 - val_categorical_accuracy: 0.7766 - 860ms/epoch - 6ms/step
Epoch 15/250
141/141 - 1s - loss: 0.5706 - categorical_accuracy: 0.7872 - val_loss: 0.6233 - val_categorical_accuracy: 0.7730 - 880ms/epoch - 6ms/step
Epoch 16/250
141/141 - 1s - loss: 0.5532 - categorical_accuracy: 0.7948 - val_loss: 0.5190 - val_categorical_accuracy: 0.8084 - 860ms/epoch - 6ms/step
Epoch 17/250
141/141 - 1s - loss: 0.5174 - categorical_accuracy: 0.8079 - val_loss: 0.4900 - val_categorical_accuracy: 0.8222 - 860ms/epoch - 6ms/step
Epoch 18/250
141/141 - 1s - loss: 0.5603 - categorical_accuracy: 0.8001 - val_loss: 0.4821 - val_categorical_accuracy: 0.8212 - 900ms/epoch - 6ms/step
Epoch 19/250
141/141 - 1s - loss: 0.4892 - categorical_accuracy: 0.8211 - val_loss: 0.5302 - val_categorical_accuracy: 0.7997 - 880ms/epoch - 6ms/step
Epoch 20/250
141/141 - 1s - loss: 0.4579 - categorical_accuracy: 0.8312 - val_loss: 0.4593 - val_categorical_accuracy: 0.8271 - 870ms/epoch - 6ms/step
Epoch 21/250
141/141 - 1s - loss: 0.4561 - categorical_accuracy: 0.8334 - val_loss: 0.4334 - val_categorical_accuracy: 0.8391 - 860ms/epoch - 6ms/step
Epoch 22/250
141/141 - 1s - loss: 0.4385 - categorical_accuracy: 0.8396 - val_loss: 0.3855 - val_categorical_accuracy: 0.8584 - 870ms/epoch - 6ms/step
Epoch 23/250
141/141 - 1s - loss: 0.4207 - categorical_accuracy: 0.8459 - val_loss: 2.3483 - val_categorical_accuracy: 0.5150 - 1s/epoch - 7ms/step
Epoch 24/250
141/141 - 1s - loss: 0.7316 - categorical_accuracy: 0.7625 - val_loss: 0.4838 - val_categorical_accuracy: 0.8189 - 870ms/epoch - 6ms/step
Epoch 25/250
141/141 - 1s - loss: 0.4487 - categorical_accuracy: 0.8415 - val_loss: 0.3720 - val_categorical_accuracy: 0.8641 - 880ms/epoch - 6ms/step
Epoch 26/250
141/141 - 1s - loss: 0.3787 - categorical_accuracy: 0.8627 - val_loss: 0.4369 - val_categorical_accuracy: 0.8408 - 870ms/epoch - 6ms/step
Epoch 27/250
141/141 - 1s - loss: 0.4212 - categorical_accuracy: 0.8523 - val_loss: 0.3757 - val_categorical_accuracy: 0.8615 - 860ms/epoch - 6ms/step
Epoch 28/250
141/141 - 1s - loss: 0.3517 - categorical_accuracy: 0.8726 - val_loss: 0.3449 - val_categorical_accuracy: 0.8742 - 870ms/epoch - 6ms/step
Epoch 29/250
141/141 - 1s - loss: 0.3522 - categorical_accuracy: 0.8734 - val_loss: 0.3782 - val_categorical_accuracy: 0.8629 - 860ms/epoch - 6ms/step
Epoch 30/250
141/141 - 1s - loss: 0.3381 - categorical_accuracy: 0.8778 - val_loss: 0.5304 - val_categorical_accuracy: 0.8177 - 860ms/epoch - 6ms/step
Epoch 31/250
141/141 - 1s - loss: 0.3334 - categorical_accuracy: 0.8804 - val_loss: 0.3067 - val_categorical_accuracy: 0.8872 - 860ms/epoch - 6ms/step
Epoch 32/250
141/141 - 1s - loss: 0.4632 - categorical_accuracy: 0.8497 - val_loss: 0.3348 - val_categorical_accuracy: 0.8789 - 860ms/epoch - 6ms/step
Epoch 33/250
141/141 - 1s - loss: 0.3114 - categorical_accuracy: 0.8876 - val_loss: 0.3770 - val_categorical_accuracy: 0.8602 - 860ms/epoch - 6ms/step
Epoch 34/250
141/141 - 1s - loss: 0.3181 - categorical_accuracy: 0.8861 - val_loss: 0.2956 - val_categorical_accuracy: 0.8951 - 860ms/epoch - 6ms/step
Epoch 35/250
141/141 - 1s - loss: 0.3076 - categorical_accuracy: 0.8909 - val_loss: 0.3213 - val_categorical_accuracy: 0.8851 - 860ms/epoch - 6ms/step
Epoch 36/250
141/141 - 1s - loss: 0.2824 - categorical_accuracy: 0.8986 - val_loss: 0.3268 - val_categorical_accuracy: 0.8785 - 860ms/epoch - 6ms/step
Epoch 37/250
141/141 - 1s - loss: 0.2819 - categorical_accuracy: 0.8992 - val_loss: 0.3014 - val_categorical_accuracy: 0.8893 - 860ms/epoch - 6ms/step
Epoch 38/250
141/141 - 1s - loss: 0.2875 - categorical_accuracy: 0.8995 - val_loss: 0.2921 - val_categorical_accuracy: 0.8914 - 860ms/epoch - 6ms/step
Epoch 39/250
141/141 - 1s - loss: 0.3138 - categorical_accuracy: 0.8946 - val_loss: 0.2777 - val_categorical_accuracy: 0.8998 - 880ms/epoch - 6ms/step
Epoch 40/250
141/141 - 1s - loss: 0.2668 - categorical_accuracy: 0.9047 - val_loss: 0.2691 - val_categorical_accuracy: 0.9032 - 870ms/epoch - 6ms/step
Epoch 41/250
141/141 - 1s - loss: 0.2533 - categorical_accuracy: 0.9093 - val_loss: 0.2800 - val_categorical_accuracy: 0.9008 - 860ms/epoch - 6ms/step
Epoch 42/250
141/141 - 1s - loss: 0.2732 - categorical_accuracy: 0.9039 - val_loss: 0.2702 - val_categorical_accuracy: 0.9036 - 870ms/epoch - 6ms/step
Epoch 43/250
141/141 - 1s - loss: 0.2577 - categorical_accuracy: 0.9092 - val_loss: 0.4130 - val_categorical_accuracy: 0.8513 - 870ms/epoch - 6ms/step
Epoch 44/250
141/141 - 1s - loss: 0.2382 - categorical_accuracy: 0.9154 - val_loss: 0.2666 - val_categorical_accuracy: 0.9046 - 860ms/epoch - 6ms/step
Epoch 45/250
141/141 - 1s - loss: 0.2353 - categorical_accuracy: 0.9165 - val_loss: 0.2644 - val_categorical_accuracy: 0.9065 - 860ms/epoch - 6ms/step
Epoch 46/250
141/141 - 1s - loss: 0.2532 - categorical_accuracy: 0.9107 - val_loss: 0.2567 - val_categorical_accuracy: 0.9098 - 860ms/epoch - 6ms/step
Epoch 47/250
141/141 - 1s - loss: 0.2215 - categorical_accuracy: 0.9217 - val_loss: 0.2550 - val_categorical_accuracy: 0.9086 - 880ms/epoch - 6ms/step
Epoch 48/250
141/141 - 1s - loss: 0.2304 - categorical_accuracy: 0.9182 - val_loss: 0.2321 - val_categorical_accuracy: 0.9174 - 860ms/epoch - 6ms/step
Epoch 49/250
141/141 - 1s - loss: 0.2976 - categorical_accuracy: 0.9036 - val_loss: 0.2474 - val_categorical_accuracy: 0.9138 - 870ms/epoch - 6ms/step
Epoch 50/250
141/141 - 1s - loss: 0.2242 - categorical_accuracy: 0.9208 - val_loss: 0.2266 - val_categorical_accuracy: 0.9204 - 870ms/epoch - 6ms/step
Epoch 51/250
141/141 - 1s - loss: 0.2163 - categorical_accuracy: 0.9235 - val_loss: 0.2297 - val_categorical_accuracy: 0.9179 - 860ms/epoch - 6ms/step
Epoch 52/250
141/141 - 1s - loss: 0.2408 - categorical_accuracy: 0.9177 - val_loss: 0.2318 - val_categorical_accuracy: 0.9202 - 870ms/epoch - 6ms/step
Epoch 53/250
141/141 - 1s - loss: 0.2091 - categorical_accuracy: 0.9270 - val_loss: 0.2202 - val_categorical_accuracy: 0.9231 - 860ms/epoch - 6ms/step
Epoch 54/250
141/141 - 1s - loss: 0.2050 - categorical_accuracy: 0.9279 - val_loss: 0.3187 - val_categorical_accuracy: 0.8830 - 870ms/epoch - 6ms/step
Epoch 55/250
141/141 - 1s - loss: 0.2171 - categorical_accuracy: 0.9234 - val_loss: 0.3011 - val_categorical_accuracy: 0.8911 - 860ms/epoch - 6ms/step
Epoch 56/250
141/141 - 1s - loss: 0.2164 - categorical_accuracy: 0.9265 - val_loss: 1.7263 - val_categorical_accuracy: 0.6103 - 870ms/epoch - 6ms/step
Epoch 57/250
141/141 - 1s - loss: 0.2276 - categorical_accuracy: 0.9224 - val_loss: 0.2157 - val_categorical_accuracy: 0.9253 - 850ms/epoch - 6ms/step
Epoch 58/250
141/141 - 1s - loss: 0.2025 - categorical_accuracy: 0.9293 - val_loss: 0.2214 - val_categorical_accuracy: 0.9205 - 870ms/epoch - 6ms/step
Epoch 59/250
141/141 - 1s - loss: 0.1934 - categorical_accuracy: 0.9327 - val_loss: 0.2844 - val_categorical_accuracy: 0.8958 - 859ms/epoch - 6ms/step
Epoch 60/250
141/141 - 1s - loss: 0.1890 - categorical_accuracy: 0.9336 - val_loss: 0.3002 - val_categorical_accuracy: 0.8968 - 870ms/epoch - 6ms/step
Epoch 61/250
141/141 - 1s - loss: 0.1859 - categorical_accuracy: 0.9348 - val_loss: 0.2573 - val_categorical_accuracy: 0.9075 - 880ms/epoch - 6ms/step
Epoch 62/250
141/141 - 1s - loss: 0.2543 - categorical_accuracy: 0.9186 - val_loss: 0.2638 - val_categorical_accuracy: 0.9030 - 860ms/epoch - 6ms/step
Epoch 63/250
141/141 - 1s - loss: 0.1808 - categorical_accuracy: 0.9367 - val_loss: 0.2399 - val_categorical_accuracy: 0.9149 - 860ms/epoch - 6ms/step
Epoch 64/250
141/141 - 1s - loss: 0.1797 - categorical_accuracy: 0.9370 - val_loss: 0.2325 - val_categorical_accuracy: 0.9164 - 870ms/epoch - 6ms/step
Epoch 65/250
141/141 - 1s - loss: 0.1798 - categorical_accuracy: 0.9375 - val_loss: 0.1910 - val_categorical_accuracy: 0.9334 - 870ms/epoch - 6ms/step
Epoch 66/250
141/141 - 1s - loss: 0.1755 - categorical_accuracy: 0.9385 - val_loss: 0.1997 - val_categorical_accuracy: 0.9311 - 860ms/epoch - 6ms/step
Epoch 67/250
141/141 - 1s - loss: 0.2752 - categorical_accuracy: 0.9160 - val_loss: 0.2077 - val_categorical_accuracy: 0.9285 - 860ms/epoch - 6ms/step
Epoch 68/250
141/141 - 1s - loss: 0.1722 - categorical_accuracy: 0.9401 - val_loss: 0.2139 - val_categorical_accuracy: 0.9235 - 880ms/epoch - 6ms/step
Epoch 69/250
141/141 - 1s - loss: 0.1754 - categorical_accuracy: 0.9399 - val_loss: 0.3055 - val_categorical_accuracy: 0.8894 - 870ms/epoch - 6ms/step
Epoch 70/250
141/141 - 1s - loss: 0.1814 - categorical_accuracy: 0.9378 - val_loss: 0.1992 - val_categorical_accuracy: 0.9294 - 860ms/epoch - 6ms/step
Epoch 71/250
141/141 - 1s - loss: 0.1624 - categorical_accuracy: 0.9441 - val_loss: 0.5714 - val_categorical_accuracy: 0.8245 - 870ms/epoch - 6ms/step
Epoch 72/250
141/141 - 1s - loss: 0.1664 - categorical_accuracy: 0.9426 - val_loss: 0.1939 - val_categorical_accuracy: 0.9335 - 860ms/epoch - 6ms/step
Epoch 73/250
141/141 - 1s - loss: 0.1640 - categorical_accuracy: 0.9425 - val_loss: 0.1832 - val_categorical_accuracy: 0.9359 - 860ms/epoch - 6ms/step
Epoch 74/250
141/141 - 1s - loss: 0.2182 - categorical_accuracy: 0.9314 - val_loss: 0.2238 - val_categorical_accuracy: 0.9209 - 860ms/epoch - 6ms/step
Epoch 75/250
141/141 - 1s - loss: 0.1533 - categorical_accuracy: 0.9469 - val_loss: 0.2924 - val_categorical_accuracy: 0.8953 - 860ms/epoch - 6ms/step
Epoch 76/250
141/141 - 1s - loss: 0.2679 - categorical_accuracy: 0.9185 - val_loss: 0.1824 - val_categorical_accuracy: 0.9367 - 870ms/epoch - 6ms/step
Epoch 77/250
141/141 - 1s - loss: 0.1553 - categorical_accuracy: 0.9461 - val_loss: 0.1815 - val_categorical_accuracy: 0.9372 - 870ms/epoch - 6ms/step
Epoch 78/250
141/141 - 1s - loss: 0.1492 - categorical_accuracy: 0.9485 - val_loss: 0.1751 - val_categorical_accuracy: 0.9402 - 870ms/epoch - 6ms/step
Epoch 79/250
141/141 - 1s - loss: 0.1539 - categorical_accuracy: 0.9469 - val_loss: 0.1846 - val_categorical_accuracy: 0.9374 - 860ms/epoch - 6ms/step
Epoch 80/250
141/141 - 1s - loss: 0.1562 - categorical_accuracy: 0.9467 - val_loss: 0.2912 - val_categorical_accuracy: 0.9020 - 860ms/epoch - 6ms/step
Epoch 81/250
141/141 - 1s - loss: 0.1588 - categorical_accuracy: 0.9464 - val_loss: 0.2336 - val_categorical_accuracy: 0.9180 - 860ms/epoch - 6ms/step
Epoch 82/250
141/141 - 1s - loss: 0.1504 - categorical_accuracy: 0.9475 - val_loss: 0.2218 - val_categorical_accuracy: 0.9217 - 860ms/epoch - 6ms/step
Epoch 83/250
141/141 - 1s - loss: 0.1810 - categorical_accuracy: 0.9420 - val_loss: 0.1957 - val_categorical_accuracy: 0.9346 - 860ms/epoch - 6ms/step
Epoch 84/250
141/141 - 1s - loss: 0.1637 - categorical_accuracy: 0.9448 - val_loss: 0.1901 - val_categorical_accuracy: 0.9359 - 860ms/epoch - 6ms/step
Epoch 85/250
141/141 - 1s - loss: 0.1396 - categorical_accuracy: 0.9518 - val_loss: 0.1881 - val_categorical_accuracy: 0.9339 - 870ms/epoch - 6ms/step
Epoch 86/250
141/141 - 1s - loss: 0.1426 - categorical_accuracy: 0.9505 - val_loss: 0.3534 - val_categorical_accuracy: 0.8849 - 870ms/epoch - 6ms/step
Epoch 87/250
141/141 - 1s - loss: 0.1430 - categorical_accuracy: 0.9502 - val_loss: 0.6327 - val_categorical_accuracy: 0.8223 - 880ms/epoch - 6ms/step
Epoch 88/250
141/141 - 1s - loss: 0.1545 - categorical_accuracy: 0.9477 - val_loss: 0.1757 - val_categorical_accuracy: 0.9406 - 880ms/epoch - 6ms/step
Epoch 89/250
141/141 - 1s - loss: 0.1327 - categorical_accuracy: 0.9543 - val_loss: 0.1898 - val_categorical_accuracy: 0.9368 - 860ms/epoch - 6ms/step
Epoch 90/250
141/141 - 1s - loss: 0.1397 - categorical_accuracy: 0.9519 - val_loss: 0.1825 - val_categorical_accuracy: 0.9401 - 870ms/epoch - 6ms/step
Epoch 91/250
141/141 - 1s - loss: 0.1349 - categorical_accuracy: 0.9537 - val_loss: 0.1800 - val_categorical_accuracy: 0.9384 - 870ms/epoch - 6ms/step
Epoch 92/250
141/141 - 1s - loss: 0.1421 - categorical_accuracy: 0.9518 - val_loss: 0.1802 - val_categorical_accuracy: 0.9380 - 860ms/epoch - 6ms/step
Epoch 93/250
141/141 - 1s - loss: 0.1468 - categorical_accuracy: 0.9504 - val_loss: 0.2131 - val_categorical_accuracy: 0.9276 - 860ms/epoch - 6ms/step
Epoch 94/250
141/141 - 1s - loss: 0.1532 - categorical_accuracy: 0.9494 - val_loss: 0.1719 - val_categorical_accuracy: 0.9441 - 870ms/epoch - 6ms/step
Epoch 95/250
141/141 - 1s - loss: 0.1433 - categorical_accuracy: 0.9511 - val_loss: 0.1752 - val_categorical_accuracy: 0.9414 - 870ms/epoch - 6ms/step
Epoch 96/250
141/141 - 1s - loss: 0.1209 - categorical_accuracy: 0.9588 - val_loss: 0.1774 - val_categorical_accuracy: 0.9390 - 860ms/epoch - 6ms/step
Epoch 97/250
141/141 - 1s - loss: 0.2660 - categorical_accuracy: 0.9225 - val_loss: 0.1727 - val_categorical_accuracy: 0.9424 - 870ms/epoch - 6ms/step
Epoch 98/250
141/141 - 1s - loss: 0.1357 - categorical_accuracy: 0.9544 - val_loss: 0.2054 - val_categorical_accuracy: 0.9270 - 860ms/epoch - 6ms/step
Epoch 99/250
141/141 - 1s - loss: 0.1337 - categorical_accuracy: 0.9553 - val_loss: 0.1802 - val_categorical_accuracy: 0.9410 - 860ms/epoch - 6ms/step
Epoch 100/250
141/141 - 1s - loss: 0.1253 - categorical_accuracy: 0.9572 - val_loss: 0.1876 - val_categorical_accuracy: 0.9356 - 860ms/epoch - 6ms/step
Epoch 101/250
141/141 - 1s - loss: 0.1189 - categorical_accuracy: 0.9590 - val_loss: 0.2905 - val_categorical_accuracy: 0.9037 - 860ms/epoch - 6ms/step
Epoch 102/250
141/141 - 1s - loss: 0.1952 - categorical_accuracy: 0.9413 - val_loss: 0.1681 - val_categorical_accuracy: 0.9413 - 860ms/epoch - 6ms/step
Epoch 103/250
141/141 - 1s - loss: 0.1212 - categorical_accuracy: 0.9584 - val_loss: 0.2031 - val_categorical_accuracy: 0.9277 - 870ms/epoch - 6ms/step
Epoch 104/250
141/141 - 1s - loss: 0.1242 - categorical_accuracy: 0.9573 - val_loss: 0.1954 - val_categorical_accuracy: 0.9333 - 860ms/epoch - 6ms/step
Epoch 105/250
141/141 - 1s - loss: 0.1429 - categorical_accuracy: 0.9525 - val_loss: 0.1584 - val_categorical_accuracy: 0.9464 - 870ms/epoch - 6ms/step
Epoch 106/250
141/141 - 1s - loss: 0.1209 - categorical_accuracy: 0.9599 - val_loss: 0.1804 - val_categorical_accuracy: 0.9368 - 860ms/epoch - 6ms/step
Epoch 107/250
141/141 - 1s - loss: 0.1445 - categorical_accuracy: 0.9512 - val_loss: 0.1761 - val_categorical_accuracy: 0.9398 - 870ms/epoch - 6ms/step
Epoch 108/250
141/141 - 1s - loss: 0.1115 - categorical_accuracy: 0.9623 - val_loss: 0.1733 - val_categorical_accuracy: 0.9402 - 870ms/epoch - 6ms/step
Epoch 109/250
141/141 - 1s - loss: 0.1858 - categorical_accuracy: 0.9434 - val_loss: 0.1742 - val_categorical_accuracy: 0.9424 - 860ms/epoch - 6ms/step
Epoch 110/250
141/141 - 1s - loss: 0.1130 - categorical_accuracy: 0.9619 - val_loss: 0.1621 - val_categorical_accuracy: 0.9456 - 860ms/epoch - 6ms/step
Epoch 111/250
141/141 - 1s - loss: 0.1256 - categorical_accuracy: 0.9578 - val_loss: 0.1605 - val_categorical_accuracy: 0.9463 - 860ms/epoch - 6ms/step
Epoch 112/250
141/141 - 1s - loss: 0.1138 - categorical_accuracy: 0.9610 - val_loss: 0.3718 - val_categorical_accuracy: 0.8803 - 870ms/epoch - 6ms/step
Epoch 113/250
141/141 - 1s - loss: 0.1264 - categorical_accuracy: 0.9581 - val_loss: 0.1744 - val_categorical_accuracy: 0.9437 - 870ms/epoch - 6ms/step
Epoch 114/250
141/141 - 1s - loss: 0.1101 - categorical_accuracy: 0.9624 - val_loss: 0.1695 - val_categorical_accuracy: 0.9430 - 860ms/epoch - 6ms/step
Epoch 115/250
141/141 - 1s - loss: 0.1174 - categorical_accuracy: 0.9598 - val_loss: 0.1869 - val_categorical_accuracy: 0.9366 - 860ms/epoch - 6ms/step
Epoch 116/250
141/141 - 1s - loss: 0.1236 - categorical_accuracy: 0.9578 - val_loss: 0.2317 - val_categorical_accuracy: 0.9249 - 870ms/epoch - 6ms/step
Epoch 117/250
141/141 - 1s - loss: 0.1080 - categorical_accuracy: 0.9632 - val_loss: 0.1798 - val_categorical_accuracy: 0.9408 - 870ms/epoch - 6ms/step
Epoch 118/250
141/141 - 1s - loss: 0.1529 - categorical_accuracy: 0.9526 - val_loss: 0.1670 - val_categorical_accuracy: 0.9447 - 860ms/epoch - 6ms/step
Epoch 119/250
141/141 - 1s - loss: 0.1049 - categorical_accuracy: 0.9645 - val_loss: 0.1681 - val_categorical_accuracy: 0.9459 - 880ms/epoch - 6ms/step
Epoch 120/250
141/141 - 1s - loss: 0.1355 - categorical_accuracy: 0.9571 - val_loss: 0.1621 - val_categorical_accuracy: 0.9458 - 860ms/epoch - 6ms/step
Epoch 121/250
141/141 - 1s - loss: 0.1031 - categorical_accuracy: 0.9649 - val_loss: 0.1749 - val_categorical_accuracy: 0.9425 - 850ms/epoch - 6ms/step
Epoch 122/250
141/141 - 1s - loss: 0.1066 - categorical_accuracy: 0.9631 - val_loss: 0.1846 - val_categorical_accuracy: 0.9402 - 860ms/epoch - 6ms/step
Epoch 123/250
141/141 - 1s - loss: 0.1300 - categorical_accuracy: 0.9573 - val_loss: 0.1786 - val_categorical_accuracy: 0.9388 - 860ms/epoch - 6ms/step
Epoch 124/250
141/141 - 1s - loss: 0.1008 - categorical_accuracy: 0.9656 - val_loss: 0.1687 - val_categorical_accuracy: 0.9424 - 860ms/epoch - 6ms/step
Epoch 125/250
141/141 - 1s - loss: 0.1145 - categorical_accuracy: 0.9610 - val_loss: 0.1612 - val_categorical_accuracy: 0.9482 - 870ms/epoch - 6ms/step
Epoch 126/250
141/141 - 1s - loss: 0.1056 - categorical_accuracy: 0.9639 - val_loss: 0.1949 - val_categorical_accuracy: 0.9335 - 860ms/epoch - 6ms/step
Epoch 127/250
141/141 - 1s - loss: 0.1043 - categorical_accuracy: 0.9642 - val_loss: 0.1641 - val_categorical_accuracy: 0.9463 - 880ms/epoch - 6ms/step
Epoch 128/250
141/141 - 1s - loss: 0.1171 - categorical_accuracy: 0.9604 - val_loss: 0.1609 - val_categorical_accuracy: 0.9468 - 860ms/epoch - 6ms/step
Epoch 129/250
141/141 - 1s - loss: 0.1309 - categorical_accuracy: 0.9583 - val_loss: 0.1697 - val_categorical_accuracy: 0.9451 - 862ms/epoch - 6ms/step
Epoch 130/250
141/141 - 1s - loss: 0.0987 - categorical_accuracy: 0.9665 - val_loss: 0.1574 - val_categorical_accuracy: 0.9489 - 870ms/epoch - 6ms/step
Epoch 131/250
141/141 - 1s - loss: 0.0950 - categorical_accuracy: 0.9674 - val_loss: 0.1743 - val_categorical_accuracy: 0.9430 - 870ms/epoch - 6ms/step
Epoch 132/250
141/141 - 1s - loss: 0.1168 - categorical_accuracy: 0.9599 - val_loss: 0.1670 - val_categorical_accuracy: 0.9444 - 860ms/epoch - 6ms/step
Epoch 133/250
141/141 - 1s - loss: 0.0975 - categorical_accuracy: 0.9669 - val_loss: 0.1855 - val_categorical_accuracy: 0.9398 - 860ms/epoch - 6ms/step
Epoch 134/250
141/141 - 1s - loss: 0.1217 - categorical_accuracy: 0.9600 - val_loss: 0.1568 - val_categorical_accuracy: 0.9481 - 880ms/epoch - 6ms/step
Epoch 135/250
141/141 - 1s - loss: 0.1099 - categorical_accuracy: 0.9635 - val_loss: 0.1947 - val_categorical_accuracy: 0.9330 - 880ms/epoch - 6ms/step
Epoch 136/250
141/141 - 1s - loss: 0.0941 - categorical_accuracy: 0.9677 - val_loss: 0.3065 - val_categorical_accuracy: 0.8960 - 870ms/epoch - 6ms/step
Epoch 137/250
141/141 - 1s - loss: 0.2292 - categorical_accuracy: 0.9345 - val_loss: 0.1614 - val_categorical_accuracy: 0.9471 - 870ms/epoch - 6ms/step
Epoch 138/250
141/141 - 1s - loss: 0.0963 - categorical_accuracy: 0.9675 - val_loss: 0.1716 - val_categorical_accuracy: 0.9448 - 860ms/epoch - 6ms/step
Epoch 139/250
141/141 - 1s - loss: 0.0941 - categorical_accuracy: 0.9677 - val_loss: 0.1581 - val_categorical_accuracy: 0.9499 - 860ms/epoch - 6ms/step
Epoch 140/250
141/141 - 1s - loss: 0.0960 - categorical_accuracy: 0.9672 - val_loss: 0.1622 - val_categorical_accuracy: 0.9484 - 860ms/epoch - 6ms/step
Epoch 141/250
141/141 - 1s - loss: 0.1680 - categorical_accuracy: 0.9499 - val_loss: 0.1740 - val_categorical_accuracy: 0.9442 - 860ms/epoch - 6ms/step
Epoch 142/250
141/141 - 1s - loss: 0.0931 - categorical_accuracy: 0.9685 - val_loss: 0.1494 - val_categorical_accuracy: 0.9523 - 880ms/epoch - 6ms/step
Epoch 143/250
141/141 - 1s - loss: 0.0931 - categorical_accuracy: 0.9679 - val_loss: 0.1586 - val_categorical_accuracy: 0.9477 - 860ms/epoch - 6ms/step
Epoch 144/250
141/141 - 1s - loss: 0.1055 - categorical_accuracy: 0.9650 - val_loss: 0.1527 - val_categorical_accuracy: 0.9514 - 860ms/epoch - 6ms/step
Epoch 145/250
141/141 - 1s - loss: 0.1025 - categorical_accuracy: 0.9660 - val_loss: 0.1575 - val_categorical_accuracy: 0.9477 - 860ms/epoch - 6ms/step
Epoch 146/250
141/141 - 1s - loss: 0.0886 - categorical_accuracy: 0.9699 - val_loss: 0.1880 - val_categorical_accuracy: 0.9364 - 860ms/epoch - 6ms/step
Epoch 147/250
141/141 - 1s - loss: 0.1025 - categorical_accuracy: 0.9648 - val_loss: 0.1569 - val_categorical_accuracy: 0.9497 - 860ms/epoch - 6ms/step
Epoch 148/250
141/141 - 1s - loss: 0.0929 - categorical_accuracy: 0.9687 - val_loss: 0.1515 - val_categorical_accuracy: 0.9519 - 870ms/epoch - 6ms/step
Epoch 149/250
141/141 - 1s - loss: 0.1377 - categorical_accuracy: 0.9574 - val_loss: 0.1817 - val_categorical_accuracy: 0.9405 - 870ms/epoch - 6ms/step
Epoch 150/250
141/141 - 1s - loss: 0.0915 - categorical_accuracy: 0.9691 - val_loss: 0.1523 - val_categorical_accuracy: 0.9534 - 860ms/epoch - 6ms/step
Epoch 151/250
141/141 - 1s - loss: 0.0942 - categorical_accuracy: 0.9679 - val_loss: 0.1625 - val_categorical_accuracy: 0.9499 - 870ms/epoch - 6ms/step
Epoch 152/250
141/141 - 1s - loss: 0.0871 - categorical_accuracy: 0.9704 - val_loss: 0.2165 - val_categorical_accuracy: 0.9357 - 870ms/epoch - 6ms/step
Epoch 153/250
141/141 - 1s - loss: 0.1222 - categorical_accuracy: 0.9616 - val_loss: 0.1568 - val_categorical_accuracy: 0.9504 - 880ms/epoch - 6ms/step
Epoch 154/250
141/141 - 1s - loss: 0.0981 - categorical_accuracy: 0.9665 - val_loss: 0.1610 - val_categorical_accuracy: 0.9489 - 860ms/epoch - 6ms/step
Epoch 155/250
141/141 - 1s - loss: 0.0863 - categorical_accuracy: 0.9705 - val_loss: 0.1591 - val_categorical_accuracy: 0.9487 - 880ms/epoch - 6ms/step
Epoch 156/250
141/141 - 1s - loss: 0.0944 - categorical_accuracy: 0.9678 - val_loss: 0.1519 - val_categorical_accuracy: 0.9522 - 870ms/epoch - 6ms/step
Epoch 157/250
141/141 - 1s - loss: 0.0853 - categorical_accuracy: 0.9709 - val_loss: 0.1672 - val_categorical_accuracy: 0.9441 - 880ms/epoch - 6ms/step
Epoch 158/250
141/141 - 1s - loss: 0.1030 - categorical_accuracy: 0.9660 - val_loss: 0.1565 - val_categorical_accuracy: 0.9523 - 880ms/epoch - 6ms/step
Epoch 159/250
141/141 - 1s - loss: 0.1058 - categorical_accuracy: 0.9655 - val_loss: 0.1554 - val_categorical_accuracy: 0.9520 - 870ms/epoch - 6ms/step
Epoch 160/250
141/141 - 1s - loss: 0.0827 - categorical_accuracy: 0.9721 - val_loss: 0.1687 - val_categorical_accuracy: 0.9471 - 860ms/epoch - 6ms/step
Epoch 161/250
141/141 - 1s - loss: 0.1070 - categorical_accuracy: 0.9645 - val_loss: 0.1518 - val_categorical_accuracy: 0.9499 - 860ms/epoch - 6ms/step
Epoch 162/250
141/141 - 1s - loss: 0.0951 - categorical_accuracy: 0.9680 - val_loss: 0.1637 - val_categorical_accuracy: 0.9465 - 860ms/epoch - 6ms/step
Epoch 163/250
141/141 - 1s - loss: 0.2225 - categorical_accuracy: 0.9371 - val_loss: 0.1748 - val_categorical_accuracy: 0.9441 - 870ms/epoch - 6ms/step
Epoch 164/250
141/141 - 1s - loss: 0.0914 - categorical_accuracy: 0.9697 - val_loss: 0.1532 - val_categorical_accuracy: 0.9514 - 870ms/epoch - 6ms/step
Epoch 165/250
141/141 - 1s - loss: 0.0820 - categorical_accuracy: 0.9723 - val_loss: 0.1580 - val_categorical_accuracy: 0.9512 - 860ms/epoch - 6ms/step
Epoch 166/250
141/141 - 1s - loss: 0.0981 - categorical_accuracy: 0.9671 - val_loss: 0.1464 - val_categorical_accuracy: 0.9529 - 880ms/epoch - 6ms/step
Epoch 167/250
141/141 - 1s - loss: 0.0874 - categorical_accuracy: 0.9704 - val_loss: 0.1566 - val_categorical_accuracy: 0.9503 - 870ms/epoch - 6ms/step
Epoch 168/250
141/141 - 1s - loss: 0.0841 - categorical_accuracy: 0.9717 - val_loss: 0.1475 - val_categorical_accuracy: 0.9541 - 860ms/epoch - 6ms/step
Epoch 169/250
141/141 - 1s - loss: 0.1028 - categorical_accuracy: 0.9675 - val_loss: 0.1519 - val_categorical_accuracy: 0.9522 - 870ms/epoch - 6ms/step
Epoch 170/250
141/141 - 1s - loss: 0.0804 - categorical_accuracy: 0.9728 - val_loss: 0.1886 - val_categorical_accuracy: 0.9420 - 870ms/epoch - 6ms/step
Epoch 171/250
141/141 - 1s - loss: 0.0823 - categorical_accuracy: 0.9717 - val_loss: 0.1803 - val_categorical_accuracy: 0.9465 - 870ms/epoch - 6ms/step
Epoch 172/250
141/141 - 1s - loss: 0.0841 - categorical_accuracy: 0.9710 - val_loss: 0.1719 - val_categorical_accuracy: 0.9493 - 850ms/epoch - 6ms/step
Epoch 173/250
141/141 - 1s - loss: 0.0880 - categorical_accuracy: 0.9710 - val_loss: 1.7797 - val_categorical_accuracy: 0.7429 - 870ms/epoch - 6ms/step
Epoch 174/250
141/141 - 1s - loss: 0.1148 - categorical_accuracy: 0.9648 - val_loss: 0.1646 - val_categorical_accuracy: 0.9492 - 860ms/epoch - 6ms/step
Epoch 175/250
141/141 - 1s - loss: 0.0786 - categorical_accuracy: 0.9733 - val_loss: 0.1862 - val_categorical_accuracy: 0.9391 - 860ms/epoch - 6ms/step
Epoch 176/250
141/141 - 1s - loss: 0.0790 - categorical_accuracy: 0.9730 - val_loss: 0.1691 - val_categorical_accuracy: 0.9471 - 860ms/epoch - 6ms/step
Epoch 177/250
141/141 - 1s - loss: 0.0947 - categorical_accuracy: 0.9678 - val_loss: 0.1837 - val_categorical_accuracy: 0.9441 - 870ms/epoch - 6ms/step
Epoch 178/250
141/141 - 1s - loss: 0.0784 - categorical_accuracy: 0.9732 - val_loss: 0.1797 - val_categorical_accuracy: 0.9419 - 850ms/epoch - 6ms/step
Epoch 179/250
141/141 - 1s - loss: 0.0778 - categorical_accuracy: 0.9734 - val_loss: 0.2073 - val_categorical_accuracy: 0.9378 - 880ms/epoch - 6ms/step
Epoch 180/250
141/141 - 1s - loss: 0.2876 - categorical_accuracy: 0.9195 - val_loss: 0.1731 - val_categorical_accuracy: 0.9436 - 860ms/epoch - 6ms/step
Epoch 181/250
141/141 - 1s - loss: 0.0820 - categorical_accuracy: 0.9720 - val_loss: 0.1576 - val_categorical_accuracy: 0.9496 - 870ms/epoch - 6ms/step
Epoch 182/250
141/141 - 1s - loss: 0.0824 - categorical_accuracy: 0.9718 - val_loss: 0.1627 - val_categorical_accuracy: 0.9482 - 860ms/epoch - 6ms/step
Epoch 183/250
141/141 - 1s - loss: 0.0770 - categorical_accuracy: 0.9737 - val_loss: 0.1815 - val_categorical_accuracy: 0.9475 - 860ms/epoch - 6ms/step
Epoch 184/250
141/141 - 1s - loss: 0.0862 - categorical_accuracy: 0.9708 - val_loss: 0.1573 - val_categorical_accuracy: 0.9524 - 870ms/epoch - 6ms/step
Epoch 185/250
141/141 - 1s - loss: 0.0936 - categorical_accuracy: 0.9683 - val_loss: 0.1649 - val_categorical_accuracy: 0.9506 - 860ms/epoch - 6ms/step
Epoch 186/250
141/141 - 1s - loss: 0.0766 - categorical_accuracy: 0.9740 - val_loss: 0.1724 - val_categorical_accuracy: 0.9474 - 860ms/epoch - 6ms/step
Epoch 187/250
141/141 - 1s - loss: 0.0771 - categorical_accuracy: 0.9740 - val_loss: 0.2095 - val_categorical_accuracy: 0.9398 - 860ms/epoch - 6ms/step
Epoch 188/250
141/141 - 1s - loss: 0.0948 - categorical_accuracy: 0.9683 - val_loss: 0.2023 - val_categorical_accuracy: 0.9379 - 880ms/epoch - 6ms/step
Epoch 189/250
141/141 - 1s - loss: 0.0874 - categorical_accuracy: 0.9712 - val_loss: 0.1880 - val_categorical_accuracy: 0.9422 - 860ms/epoch - 6ms/step
Epoch 190/250
141/141 - 1s - loss: 0.0779 - categorical_accuracy: 0.9734 - val_loss: 0.1645 - val_categorical_accuracy: 0.9519 - 870ms/epoch - 6ms/step
Epoch 191/250
141/141 - 1s - loss: 0.1070 - categorical_accuracy: 0.9646 - val_loss: 0.1874 - val_categorical_accuracy: 0.9446 - 870ms/epoch - 6ms/step
Epoch 192/250
141/141 - 1s - loss: 0.0758 - categorical_accuracy: 0.9741 - val_loss: 0.1571 - val_categorical_accuracy: 0.9508 - 860ms/epoch - 6ms/step
Epoch 193/250
141/141 - 1s - loss: 0.0748 - categorical_accuracy: 0.9746 - val_loss: 0.1629 - val_categorical_accuracy: 0.9508 - 880ms/epoch - 6ms/step
Epoch 194/250
141/141 - 1s - loss: 0.0754 - categorical_accuracy: 0.9747 - val_loss: 0.1620 - val_categorical_accuracy: 0.9522 - 860ms/epoch - 6ms/step
Epoch 195/250
141/141 - 1s - loss: 0.0740 - categorical_accuracy: 0.9746 - val_loss: 0.1866 - val_categorical_accuracy: 0.9427 - 870ms/epoch - 6ms/step
Epoch 196/250
141/141 - 1s - loss: 0.0788 - categorical_accuracy: 0.9731 - val_loss: 0.1575 - val_categorical_accuracy: 0.9536 - 870ms/epoch - 6ms/step
Epoch 197/250
141/141 - 1s - loss: 0.0891 - categorical_accuracy: 0.9695 - val_loss: 0.1710 - val_categorical_accuracy: 0.9508 - 860ms/epoch - 6ms/step
Epoch 198/250
141/141 - 1s - loss: 0.0735 - categorical_accuracy: 0.9751 - val_loss: 0.1884 - val_categorical_accuracy: 0.9472 - 863ms/epoch - 6ms/step
Epoch 199/250
141/141 - 1s - loss: 0.0736 - categorical_accuracy: 0.9749 - val_loss: 0.1901 - val_categorical_accuracy: 0.9474 - 870ms/epoch - 6ms/step
Epoch 200/250
141/141 - 1s - loss: 0.0744 - categorical_accuracy: 0.9747 - val_loss: 0.1578 - val_categorical_accuracy: 0.9538 - 870ms/epoch - 6ms/step
Epoch 201/250
141/141 - 1s - loss: 0.0959 - categorical_accuracy: 0.9694 - val_loss: 0.1740 - val_categorical_accuracy: 0.9469 - 870ms/epoch - 6ms/step
Epoch 202/250
141/141 - 1s - loss: 0.0995 - categorical_accuracy: 0.9692 - val_loss: 0.1584 - val_categorical_accuracy: 0.9491 - 860ms/epoch - 6ms/step
Epoch 203/250
141/141 - 1s - loss: 0.0706 - categorical_accuracy: 0.9761 - val_loss: 0.1576 - val_categorical_accuracy: 0.9524 - 870ms/epoch - 6ms/step
Epoch 204/250
141/141 - 1s - loss: 0.0738 - categorical_accuracy: 0.9751 - val_loss: 0.1562 - val_categorical_accuracy: 0.9538 - 870ms/epoch - 6ms/step
Epoch 205/250
141/141 - 1s - loss: 0.1096 - categorical_accuracy: 0.9665 - val_loss: 0.1739 - val_categorical_accuracy: 0.9484 - 860ms/epoch - 6ms/step
Epoch 206/250
141/141 - 1s - loss: 0.0707 - categorical_accuracy: 0.9764 - val_loss: 0.1576 - val_categorical_accuracy: 0.9500 - 860ms/epoch - 6ms/step
Epoch 207/250
141/141 - 1s - loss: 0.0994 - categorical_accuracy: 0.9688 - val_loss: 0.1731 - val_categorical_accuracy: 0.9497 - 860ms/epoch - 6ms/step
Epoch 208/250
141/141 - 1s - loss: 0.0714 - categorical_accuracy: 0.9758 - val_loss: 0.1796 - val_categorical_accuracy: 0.9497 - 870ms/epoch - 6ms/step
Epoch 209/250
141/141 - 1s - loss: 0.0685 - categorical_accuracy: 0.9769 - val_loss: 0.1515 - val_categorical_accuracy: 0.9547 - 860ms/epoch - 6ms/step
Epoch 210/250
141/141 - 1s - loss: 0.0761 - categorical_accuracy: 0.9741 - val_loss: 1.1935 - val_categorical_accuracy: 0.7700 - 860ms/epoch - 6ms/step
Epoch 211/250
141/141 - 1s - loss: 0.0947 - categorical_accuracy: 0.9699 - val_loss: 0.1655 - val_categorical_accuracy: 0.9495 - 880ms/epoch - 6ms/step
Epoch 212/250
141/141 - 1s - loss: 0.0704 - categorical_accuracy: 0.9759 - val_loss: 0.1625 - val_categorical_accuracy: 0.9529 - 870ms/epoch - 6ms/step
Epoch 213/250
141/141 - 1s - loss: 0.0747 - categorical_accuracy: 0.9743 - val_loss: 0.1987 - val_categorical_accuracy: 0.9399 - 870ms/epoch - 6ms/step
Epoch 214/250
141/141 - 1s - loss: 0.0727 - categorical_accuracy: 0.9750 - val_loss: 0.3395 - val_categorical_accuracy: 0.9156 - 860ms/epoch - 6ms/step
Epoch 215/250
141/141 - 1s - loss: 0.1054 - categorical_accuracy: 0.9677 - val_loss: 0.1611 - val_categorical_accuracy: 0.9528 - 860ms/epoch - 6ms/step
Epoch 216/250
141/141 - 1s - loss: 0.0714 - categorical_accuracy: 0.9756 - val_loss: 0.1716 - val_categorical_accuracy: 0.9496 - 870ms/epoch - 6ms/step
Epoch 217/250
141/141 - 1s - loss: 0.0693 - categorical_accuracy: 0.9763 - val_loss: 0.1554 - val_categorical_accuracy: 0.9545 - 870ms/epoch - 6ms/step
Epoch 218/250
141/141 - 1s - loss: 0.0984 - categorical_accuracy: 0.9696 - val_loss: 0.1704 - val_categorical_accuracy: 0.9456 - 860ms/epoch - 6ms/step
Epoch 219/250
141/141 - 1s - loss: 0.0671 - categorical_accuracy: 0.9773 - val_loss: 0.1517 - val_categorical_accuracy: 0.9568 - 870ms/epoch - 6ms/step
Epoch 220/250
141/141 - 1s - loss: 0.1037 - categorical_accuracy: 0.9677 - val_loss: 0.1547 - val_categorical_accuracy: 0.9542 - 870ms/epoch - 6ms/step
Epoch 221/250
141/141 - 1s - loss: 0.0678 - categorical_accuracy: 0.9770 - val_loss: 0.1677 - val_categorical_accuracy: 0.9489 - 880ms/epoch - 6ms/step
Epoch 222/250
141/141 - 1s - loss: 0.1230 - categorical_accuracy: 0.9641 - val_loss: 0.1591 - val_categorical_accuracy: 0.9527 - 860ms/epoch - 6ms/step
Epoch 223/250
141/141 - 1s - loss: 0.0675 - categorical_accuracy: 0.9773 - val_loss: 0.1644 - val_categorical_accuracy: 0.9536 - 870ms/epoch - 6ms/step
Epoch 224/250
141/141 - 1s - loss: 0.0675 - categorical_accuracy: 0.9771 - val_loss: 0.1580 - val_categorical_accuracy: 0.9548 - 890ms/epoch - 6ms/step
Epoch 225/250
141/141 - 1s - loss: 0.0681 - categorical_accuracy: 0.9766 - val_loss: 0.1621 - val_categorical_accuracy: 0.9554 - 870ms/epoch - 6ms/step
Epoch 226/250
141/141 - 1s - loss: 0.0686 - categorical_accuracy: 0.9766 - val_loss: 0.1713 - val_categorical_accuracy: 0.9495 - 880ms/epoch - 6ms/step
Epoch 227/250
141/141 - 1s - loss: 0.0705 - categorical_accuracy: 0.9761 - val_loss: 0.1692 - val_categorical_accuracy: 0.9498 - 870ms/epoch - 6ms/step
Epoch 228/250
141/141 - 1s - loss: 0.0676 - categorical_accuracy: 0.9771 - val_loss: 0.1874 - val_categorical_accuracy: 0.9446 - 870ms/epoch - 6ms/step
Epoch 229/250
141/141 - 1s - loss: 0.0669 - categorical_accuracy: 0.9771 - val_loss: 0.1672 - val_categorical_accuracy: 0.9512 - 860ms/epoch - 6ms/step
Epoch 230/250
141/141 - 1s - loss: 0.1379 - categorical_accuracy: 0.9605 - val_loss: 0.1598 - val_categorical_accuracy: 0.9535 - 860ms/epoch - 6ms/step
Epoch 231/250
141/141 - 1s - loss: 0.0657 - categorical_accuracy: 0.9777 - val_loss: 0.1580 - val_categorical_accuracy: 0.9536 - 870ms/epoch - 6ms/step
Epoch 232/250
141/141 - 1s - loss: 0.0664 - categorical_accuracy: 0.9772 - val_loss: 0.2148 - val_categorical_accuracy: 0.9340 - 860ms/epoch - 6ms/step
Epoch 233/250
141/141 - 1s - loss: 0.0919 - categorical_accuracy: 0.9710 - val_loss: 0.1662 - val_categorical_accuracy: 0.9497 - 860ms/epoch - 6ms/step
Epoch 234/250
141/141 - 1s - loss: 0.0667 - categorical_accuracy: 0.9771 - val_loss: 0.1539 - val_categorical_accuracy: 0.9555 - 860ms/epoch - 6ms/step
Epoch 235/250
141/141 - 1s - loss: 0.0700 - categorical_accuracy: 0.9761 - val_loss: 0.1631 - val_categorical_accuracy: 0.9532 - 880ms/epoch - 6ms/step
Epoch 236/250
141/141 - 1s - loss: 0.0668 - categorical_accuracy: 0.9771 - val_loss: 0.1625 - val_categorical_accuracy: 0.9553 - 870ms/epoch - 6ms/step
Epoch 237/250
141/141 - 1s - loss: 0.0660 - categorical_accuracy: 0.9775 - val_loss: 0.1784 - val_categorical_accuracy: 0.9496 - 860ms/epoch - 6ms/step
Epoch 238/250
141/141 - 1s - loss: 0.1384 - categorical_accuracy: 0.9604 - val_loss: 0.1634 - val_categorical_accuracy: 0.9552 - 860ms/epoch - 6ms/step
Epoch 239/250
141/141 - 1s - loss: 0.0664 - categorical_accuracy: 0.9773 - val_loss: 0.1596 - val_categorical_accuracy: 0.9539 - 880ms/epoch - 6ms/step
Epoch 240/250
141/141 - 1s - loss: 0.0661 - categorical_accuracy: 0.9773 - val_loss: 0.1604 - val_categorical_accuracy: 0.9554 - 860ms/epoch - 6ms/step
Epoch 241/250
141/141 - 1s - loss: 0.0646 - categorical_accuracy: 0.9780 - val_loss: 0.1756 - val_categorical_accuracy: 0.9470 - 860ms/epoch - 6ms/step
Epoch 242/250
141/141 - 1s - loss: 0.0918 - categorical_accuracy: 0.9707 - val_loss: 0.1633 - val_categorical_accuracy: 0.9517 - 870ms/epoch - 6ms/step
Epoch 243/250
141/141 - 1s - loss: 0.0636 - categorical_accuracy: 0.9783 - val_loss: 0.1906 - val_categorical_accuracy: 0.9399 - 870ms/epoch - 6ms/step
Epoch 244/250
141/141 - 1s - loss: 0.0642 - categorical_accuracy: 0.9779 - val_loss: 0.1599 - val_categorical_accuracy: 0.9574 - 880ms/epoch - 6ms/step
Epoch 245/250
141/141 - 1s - loss: 0.0622 - categorical_accuracy: 0.9787 - val_loss: 0.1518 - val_categorical_accuracy: 0.9580 - 880ms/epoch - 6ms/step
Epoch 246/250
141/141 - 1s - loss: 0.0717 - categorical_accuracy: 0.9756 - val_loss: 0.1657 - val_categorical_accuracy: 0.9536 - 1s/epoch - 7ms/step
Epoch 247/250
141/141 - 1s - loss: 0.0845 - categorical_accuracy: 0.9723 - val_loss: 0.1529 - val_categorical_accuracy: 0.9569 - 870ms/epoch - 6ms/step
Epoch 248/250
141/141 - 1s - loss: 0.0642 - categorical_accuracy: 0.9778 - val_loss: 0.1729 - val_categorical_accuracy: 0.9514 - 870ms/epoch - 6ms/step
Epoch 249/250
141/141 - 1s - loss: 0.0774 - categorical_accuracy: 0.9745 - val_loss: 0.1659 - val_categorical_accuracy: 0.9513 - 880ms/epoch - 6ms/step
Epoch 250/250
141/141 - 1s - loss: 0.0653 - categorical_accuracy: 0.9779 - val_loss: 0.1674 - val_categorical_accuracy: 0.9514 - 860ms/epoch - 6ms/step

#reticulate::py_last_error()

#We can then compute the average of the per-epoch ACC scores for all folds:

write.csv(train_targets, "../Doc/Versuch 8_1 - 250 Epochs - Smote/train_targets.csv", row.names=FALSE)

Error in file(file, ifelse(append, "a", "w")) : 
  cannot open the connection